vpx/vp8/encoder/encodemb.c

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/*
* Copyright (c) 2010 The WebM project authors. All Rights Reserved.
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*
* Use of this source code is governed by a BSD-style license
* that can be found in the LICENSE file in the root of the source
* tree. An additional intellectual property rights grant can be found
* in the file PATENTS. All contributing project authors may
* be found in the AUTHORS file in the root of the source tree.
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*/
#include "vpx_ports/config.h"
#include "encodemb.h"
#include "vp8/common/reconinter.h"
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#include "quantize.h"
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
#include "tokenize.h"
#include "vp8/common/invtrans.h"
#include "vp8/common/recon.h"
#include "vp8/common/reconintra.h"
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#include "dct.h"
#include "vpx_mem/vpx_mem.h"
#if CONFIG_RUNTIME_CPU_DETECT
#define IF_RTCD(x) (x)
#else
#define IF_RTCD(x) NULL
#endif
void vp8_subtract_b_c(BLOCK *be, BLOCKD *bd, int pitch)
{
unsigned char *src_ptr = (*(be->base_src) + be->src);
short *diff_ptr = be->src_diff;
unsigned char *pred_ptr = bd->predictor;
int src_stride = be->src_stride;
int r, c;
for (r = 0; r < 4; r++)
{
for (c = 0; c < 4; c++)
{
diff_ptr[c] = src_ptr[c] - pred_ptr[c];
}
diff_ptr += pitch;
pred_ptr += pitch;
src_ptr += src_stride;
}
}
void vp8_subtract_mbuv_c(short *diff, unsigned char *usrc, unsigned char *vsrc, unsigned char *pred, int stride)
{
short *udiff = diff + 256;
short *vdiff = diff + 320;
unsigned char *upred = pred + 256;
unsigned char *vpred = pred + 320;
int r, c;
for (r = 0; r < 8; r++)
{
for (c = 0; c < 8; c++)
{
udiff[c] = usrc[c] - upred[c];
}
udiff += 8;
upred += 8;
usrc += stride;
}
for (r = 0; r < 8; r++)
{
for (c = 0; c < 8; c++)
{
vdiff[c] = vsrc[c] - vpred[c];
}
vdiff += 8;
vpred += 8;
vsrc += stride;
}
}
void vp8_subtract_mby_c(short *diff, unsigned char *src, unsigned char *pred, int stride)
{
int r, c;
for (r = 0; r < 16; r++)
{
for (c = 0; c < 16; c++)
{
diff[c] = src[c] - pred[c];
}
diff += 16;
pred += 16;
src += stride;
}
}
static void vp8_subtract_mb(const VP8_ENCODER_RTCD *rtcd, MACROBLOCK *x)
{
ENCODEMB_INVOKE(&rtcd->encodemb, submby)(x->src_diff, x->src.y_buffer, x->e_mbd.predictor, x->src.y_stride);
ENCODEMB_INVOKE(&rtcd->encodemb, submbuv)(x->src_diff, x->src.u_buffer, x->src.v_buffer, x->e_mbd.predictor, x->src.uv_stride);
}
void vp8_build_dcblock(MACROBLOCK *x)
{
short *src_diff_ptr = &x->src_diff[384];
int i;
for (i = 0; i < 16; i++)
{
src_diff_ptr[i] = x->coeff[i * 16];
}
}
void vp8_transform_mbuv(MACROBLOCK *x)
{
int i;
for (i = 16; i < 24; i += 2)
{
x->vp8_short_fdct8x4(&x->block[i].src_diff[0],
&x->block[i].coeff[0], 16);
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}
}
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void vp8_transform_intra_mby(MACROBLOCK *x)
{
int i;
for (i = 0; i < 16; i += 2)
{
x->vp8_short_fdct8x4(&x->block[i].src_diff[0],
&x->block[i].coeff[0], 32);
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}
// build dc block from 16 y dc values
vp8_build_dcblock(x);
// do 2nd order transform on the dc block
x->short_walsh4x4(&x->block[24].src_diff[0],
&x->block[24].coeff[0], 8);
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}
void vp8_transform_mb(MACROBLOCK *x)
{
int i;
for (i = 0; i < 16; i += 2)
{
x->vp8_short_fdct8x4(&x->block[i].src_diff[0],
&x->block[i].coeff[0], 32);
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}
// build dc block from 16 y dc values
if (x->e_mbd.mode_info_context->mbmi.mode != SPLITMV)
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vp8_build_dcblock(x);
for (i = 16; i < 24; i += 2)
{
x->vp8_short_fdct8x4(&x->block[i].src_diff[0],
&x->block[i].coeff[0], 16);
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}
// do 2nd order transform on the dc block
if (x->e_mbd.mode_info_context->mbmi.mode != SPLITMV)
x->short_walsh4x4(&x->block[24].src_diff[0],
&x->block[24].coeff[0], 8);
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}
void vp8_transform_mby(MACROBLOCK *x)
{
int i;
for (i = 0; i < 16; i += 2)
{
x->vp8_short_fdct8x4(&x->block[i].src_diff[0],
&x->block[i].coeff[0], 32);
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}
// build dc block from 16 y dc values
if (x->e_mbd.mode_info_context->mbmi.mode != SPLITMV)
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{
vp8_build_dcblock(x);
x->short_walsh4x4(&x->block[24].src_diff[0],
&x->block[24].coeff[0], 8);
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}
}
void vp8_stuff_inter16x16(MACROBLOCK *x)
{
vp8_build_inter_predictors_mb_s(&x->e_mbd);
/*
// recon = copy from predictors to destination
{
BLOCKD *b = &x->e_mbd.block[0];
unsigned char *pred_ptr = b->predictor;
unsigned char *dst_ptr = *(b->base_dst) + b->dst;
int stride = b->dst_stride;
int i;
for(i=0;i<16;i++)
vpx_memcpy(dst_ptr+i*stride,pred_ptr+16*i,16);
b = &x->e_mbd.block[16];
pred_ptr = b->predictor;
dst_ptr = *(b->base_dst) + b->dst;
stride = b->dst_stride;
for(i=0;i<8;i++)
vpx_memcpy(dst_ptr+i*stride,pred_ptr+8*i,8);
b = &x->e_mbd.block[20];
pred_ptr = b->predictor;
dst_ptr = *(b->base_dst) + b->dst;
stride = b->dst_stride;
for(i=0;i<8;i++)
vpx_memcpy(dst_ptr+i*stride,pred_ptr+8*i,8);
}
*/
}
#if !(CONFIG_REALTIME_ONLY)
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
#define RDCOST(RM,DM,R,D) ( ((128+(R)*(RM)) >> 8) + (DM)*(D) )
#define RDTRUNC(RM,DM,R,D) ( (128+(R)*(RM)) & 0xFF )
typedef struct vp8_token_state vp8_token_state;
struct vp8_token_state{
int rate;
int error;
signed char next;
signed char token;
short qc;
};
// TODO: experiments to find optimal multiple numbers
#define Y1_RD_MULT 4
#define UV_RD_MULT 2
#define Y2_RD_MULT 16
static const int plane_rd_mult[4]=
{
Y1_RD_MULT,
Y2_RD_MULT,
UV_RD_MULT,
Y1_RD_MULT
};
void vp8_optimize_b(MACROBLOCK *mb, int ib, int type,
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
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ENTROPY_CONTEXT *a, ENTROPY_CONTEXT *l,
const VP8_ENCODER_RTCD *rtcd)
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{
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
BLOCK *b;
BLOCKD *d;
vp8_token_state tokens[17][2];
unsigned best_mask[2];
const short *dequant_ptr;
const short *coeff_ptr;
short *qcoeff_ptr;
short *dqcoeff_ptr;
int eob;
int i0;
int rc;
int x;
int sz;
int next;
int rdmult;
int rddiv;
int final_eob;
int rd_cost0;
int rd_cost1;
int rate0;
int rate1;
int error0;
int error1;
int t0;
int t1;
int best;
int band;
int pt;
int i;
int err_mult = plane_rd_mult[type];
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
b = &mb->block[ib];
d = &mb->e_mbd.block[ib];
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
/* Enable this to test the effect of RDO as a replacement for the dynamic
* zero bin instead of an augmentation of it.
*/
#if 0
vp8_strict_quantize_b(b, d);
#endif
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dequant_ptr = d->dequant;
coeff_ptr = b->coeff;
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
qcoeff_ptr = d->qcoeff;
dqcoeff_ptr = d->dqcoeff;
i0 = !type;
eob = d->eob;
/* Now set up a Viterbi trellis to evaluate alternative roundings. */
rdmult = mb->rdmult * err_mult;
if(mb->e_mbd.mode_info_context->mbmi.ref_frame==INTRA_FRAME)
rdmult = (rdmult * 9)>>4;
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
rddiv = mb->rddiv;
best_mask[0] = best_mask[1] = 0;
/* Initialize the sentinel node of the trellis. */
tokens[eob][0].rate = 0;
tokens[eob][0].error = 0;
tokens[eob][0].next = 16;
tokens[eob][0].token = DCT_EOB_TOKEN;
tokens[eob][0].qc = 0;
*(tokens[eob] + 1) = *(tokens[eob] + 0);
next = eob;
for (i = eob; i-- > i0;)
{
int base_bits;
int d2;
int dx;
rc = vp8_default_zig_zag1d[i];
x = qcoeff_ptr[rc];
/* Only add a trellis state for non-zero coefficients. */
if (x)
2010-05-18 17:58:33 +02:00
{
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
int shortcut=0;
error0 = tokens[next][0].error;
error1 = tokens[next][1].error;
/* Evaluate the first possibility for this state. */
rate0 = tokens[next][0].rate;
rate1 = tokens[next][1].rate;
t0 = (vp8_dct_value_tokens_ptr + x)->Token;
/* Consider both possible successor states. */
if (next < 16)
2010-05-18 17:58:33 +02:00
{
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
band = vp8_coef_bands[i + 1];
pt = vp8_prev_token_class[t0];
rate0 +=
mb->token_costs[type][band][pt][tokens[next][0].token];
rate1 +=
mb->token_costs[type][band][pt][tokens[next][1].token];
2010-05-18 17:58:33 +02:00
}
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
rd_cost0 = RDCOST(rdmult, rddiv, rate0, error0);
rd_cost1 = RDCOST(rdmult, rddiv, rate1, error1);
if (rd_cost0 == rd_cost1)
2010-05-18 17:58:33 +02:00
{
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
rd_cost0 = RDTRUNC(rdmult, rddiv, rate0, error0);
rd_cost1 = RDTRUNC(rdmult, rddiv, rate1, error1);
2010-05-18 17:58:33 +02:00
}
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
/* And pick the best. */
best = rd_cost1 < rd_cost0;
base_bits = *(vp8_dct_value_cost_ptr + x);
dx = dqcoeff_ptr[rc] - coeff_ptr[rc];
d2 = dx*dx;
tokens[i][0].rate = base_bits + (best ? rate1 : rate0);
tokens[i][0].error = d2 + (best ? error1 : error0);
tokens[i][0].next = next;
tokens[i][0].token = t0;
tokens[i][0].qc = x;
best_mask[0] |= best << i;
/* Evaluate the second possibility for this state. */
rate0 = tokens[next][0].rate;
rate1 = tokens[next][1].rate;
if((abs(x)*dequant_ptr[rc]>abs(coeff_ptr[rc])) &&
(abs(x)*dequant_ptr[rc]<abs(coeff_ptr[rc])+dequant_ptr[rc]))
shortcut = 1;
else
shortcut = 0;
if(shortcut)
2010-05-18 17:58:33 +02:00
{
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
sz = -(x < 0);
x -= 2*sz + 1;
}
2010-05-18 17:58:33 +02:00
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
/* Consider both possible successor states. */
if (!x)
{
/* If we reduced this coefficient to zero, check to see if
* we need to move the EOB back here.
*/
t0 = tokens[next][0].token == DCT_EOB_TOKEN ?
DCT_EOB_TOKEN : ZERO_TOKEN;
t1 = tokens[next][1].token == DCT_EOB_TOKEN ?
DCT_EOB_TOKEN : ZERO_TOKEN;
}
else
{
t0=t1 = (vp8_dct_value_tokens_ptr + x)->Token;
}
if (next < 16)
{
band = vp8_coef_bands[i + 1];
if(t0!=DCT_EOB_TOKEN)
2010-05-18 17:58:33 +02:00
{
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
pt = vp8_prev_token_class[t0];
rate0 += mb->token_costs[type][band][pt][
tokens[next][0].token];
2010-05-18 17:58:33 +02:00
}
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
if(t1!=DCT_EOB_TOKEN)
2010-05-18 17:58:33 +02:00
{
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
pt = vp8_prev_token_class[t1];
rate1 += mb->token_costs[type][band][pt][
tokens[next][1].token];
2010-05-18 17:58:33 +02:00
}
}
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
rd_cost0 = RDCOST(rdmult, rddiv, rate0, error0);
rd_cost1 = RDCOST(rdmult, rddiv, rate1, error1);
if (rd_cost0 == rd_cost1)
2010-05-18 17:58:33 +02:00
{
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
rd_cost0 = RDTRUNC(rdmult, rddiv, rate0, error0);
rd_cost1 = RDTRUNC(rdmult, rddiv, rate1, error1);
2010-05-18 17:58:33 +02:00
}
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
/* And pick the best. */
best = rd_cost1 < rd_cost0;
base_bits = *(vp8_dct_value_cost_ptr + x);
2010-05-18 17:58:33 +02:00
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
if(shortcut)
2010-05-18 17:58:33 +02:00
{
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
dx -= (dequant_ptr[rc] + sz) ^ sz;
d2 = dx*dx;
2010-05-18 17:58:33 +02:00
}
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
tokens[i][1].rate = base_bits + (best ? rate1 : rate0);
tokens[i][1].error = d2 + (best ? error1 : error0);
tokens[i][1].next = next;
tokens[i][1].token =best?t1:t0;
tokens[i][1].qc = x;
best_mask[1] |= best << i;
/* Finally, make this the new head of the trellis. */
next = i;
2010-05-18 17:58:33 +02:00
}
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
/* There's no choice to make for a zero coefficient, so we don't
* add a new trellis node, but we do need to update the costs.
*/
2010-05-18 17:58:33 +02:00
else
{
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
band = vp8_coef_bands[i + 1];
t0 = tokens[next][0].token;
t1 = tokens[next][1].token;
/* Update the cost of each path if we're past the EOB token. */
if (t0 != DCT_EOB_TOKEN)
{
tokens[next][0].rate += mb->token_costs[type][band][0][t0];
tokens[next][0].token = ZERO_TOKEN;
}
if (t1 != DCT_EOB_TOKEN)
{
tokens[next][1].rate += mb->token_costs[type][band][0][t1];
tokens[next][1].token = ZERO_TOKEN;
}
/* Don't update next, because we didn't add a new node. */
2010-05-18 17:58:33 +02:00
}
}
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
/* Now pick the best path through the whole trellis. */
band = vp8_coef_bands[i + 1];
VP8_COMBINEENTROPYCONTEXTS(pt, *a, *l);
rate0 = tokens[next][0].rate;
rate1 = tokens[next][1].rate;
error0 = tokens[next][0].error;
error1 = tokens[next][1].error;
t0 = tokens[next][0].token;
t1 = tokens[next][1].token;
rate0 += mb->token_costs[type][band][pt][t0];
rate1 += mb->token_costs[type][band][pt][t1];
rd_cost0 = RDCOST(rdmult, rddiv, rate0, error0);
rd_cost1 = RDCOST(rdmult, rddiv, rate1, error1);
if (rd_cost0 == rd_cost1)
{
rd_cost0 = RDTRUNC(rdmult, rddiv, rate0, error0);
rd_cost1 = RDTRUNC(rdmult, rddiv, rate1, error1);
}
best = rd_cost1 < rd_cost0;
final_eob = i0 - 1;
for (i = next; i < eob; i = next)
{
x = tokens[i][best].qc;
if (x)
final_eob = i;
rc = vp8_default_zig_zag1d[i];
qcoeff_ptr[rc] = x;
dqcoeff_ptr[rc] = x * dequant_ptr[rc];
next = tokens[i][best].next;
best = (best_mask[best] >> i) & 1;
}
final_eob++;
d->eob = final_eob;
*a = *l = (d->eob != !type);
2010-05-18 17:58:33 +02:00
}
void vp8_optimize_mb(MACROBLOCK *x, const VP8_ENCODER_RTCD *rtcd)
{
int b;
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
int type;
int has_2nd_order;
ENTROPY_CONTEXT_PLANES t_above, t_left;
ENTROPY_CONTEXT *ta;
ENTROPY_CONTEXT *tl;
vpx_memcpy(&t_above, x->e_mbd.above_context, sizeof(ENTROPY_CONTEXT_PLANES));
vpx_memcpy(&t_left, x->e_mbd.left_context, sizeof(ENTROPY_CONTEXT_PLANES));
ta = (ENTROPY_CONTEXT *)&t_above;
tl = (ENTROPY_CONTEXT *)&t_left;
2010-05-18 17:58:33 +02:00
has_2nd_order = (x->e_mbd.mode_info_context->mbmi.mode != B_PRED
&& x->e_mbd.mode_info_context->mbmi.mode != SPLITMV);
type = has_2nd_order ? PLANE_TYPE_Y_NO_DC : PLANE_TYPE_Y_WITH_DC;
2010-05-18 17:58:33 +02:00
for (b = 0; b < 16; b++)
{
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
vp8_optimize_b(x, b, type,
ta + vp8_block2above[b], tl + vp8_block2left[b], rtcd);
2010-05-18 17:58:33 +02:00
}
for (b = 16; b < 24; b++)
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{
vp8_optimize_b(x, b, PLANE_TYPE_UV,
ta + vp8_block2above[b], tl + vp8_block2left[b], rtcd);
2010-05-18 17:58:33 +02:00
}
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
if (has_2nd_order)
{
b=24;
vp8_optimize_b(x, b, PLANE_TYPE_Y2,
ta + vp8_block2above[b], tl + vp8_block2left[b], rtcd);
2010-05-18 17:58:33 +02:00
}
}
void vp8_optimize_mby(MACROBLOCK *x, const VP8_ENCODER_RTCD *rtcd)
{
int b;
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
int type;
int has_2nd_order;
2010-05-18 17:58:33 +02:00
ENTROPY_CONTEXT_PLANES t_above, t_left;
ENTROPY_CONTEXT *ta;
ENTROPY_CONTEXT *tl;
if (!x->e_mbd.above_context)
2010-05-18 17:58:33 +02:00
return;
if (!x->e_mbd.left_context)
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return;
vpx_memcpy(&t_above, x->e_mbd.above_context, sizeof(ENTROPY_CONTEXT_PLANES));
vpx_memcpy(&t_left, x->e_mbd.left_context, sizeof(ENTROPY_CONTEXT_PLANES));
ta = (ENTROPY_CONTEXT *)&t_above;
tl = (ENTROPY_CONTEXT *)&t_left;
has_2nd_order = (x->e_mbd.mode_info_context->mbmi.mode != B_PRED
&& x->e_mbd.mode_info_context->mbmi.mode != SPLITMV);
type = has_2nd_order ? PLANE_TYPE_Y_NO_DC : PLANE_TYPE_Y_WITH_DC;
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for (b = 0; b < 16; b++)
{
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
vp8_optimize_b(x, b, type,
ta + vp8_block2above[b], tl + vp8_block2left[b], rtcd);
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}
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
if (has_2nd_order)
{
b=24;
vp8_optimize_b(x, b, PLANE_TYPE_Y2,
ta + vp8_block2above[b], tl + vp8_block2left[b], rtcd);
Add trellis quantization. Replace the exponential search for optimal rounding during quantization with a linear Viterbi trellis and enable it by default when using --best. Right now this operates on top of the output of the adaptive zero-bin quantizer in vp8_regular_quantize_b() and gives a small gain. It can be tested as a replacement for that quantizer by enabling the call to vp8_strict_quantize_b(), which uses normal rounding and no zero bin offset. Ultimately, the quantizer will have to become a function of lambda in order to take advantage of activity masking, since there is limited ability to change the quantization factor itself. However, currently vp8_strict_quantize_b() plus the trellis quantizer (which is lambda-dependent) loses to vp8_regular_quantize_b() alone (which is not) on my test clip. Patch Set 3: Fix an issue related to the cost evaluation of successor states when a coefficient is reduced to zero. With this issue fixed, now the trellis search almost exactly matches the exponential search. Patch Set 2: Overall, the goal of this patch set is to make "trellis" search to produce encodings that match the exponential search version. There are three main differences between Patch Set 2 and 1: a. Patch set 1 did not properly account for the scale of 2nd order error, so patch set 2 disable it all together for 2nd blocks. b. Patch set 1 was not consistent on when to enable the the quantization optimization. Patch set 2 restore the condition to be consistent. c. Patch set 1 checks quantized level L-1, and L for any input coefficient was quantized to L. Patch set 2 limits the candidate coefficient to those that were rounded up to L. It is worth noting here that a strategy to check L and L+1 for coefficients that were truncated down to L might work. (a and b get trellis quant to basically match the exponential search on all mid/low rate encodings on cif set, without a, b, trellis quant can hurt the psnr by 0.2 to .3db at 200kbps for some cif clips) (c gets trellis quant to match the exponential search to match at Q0 encoding, without c, trellis quant can be 1.5 to 2db lower for encodings with fixed Q at 0 on most derf cif clips) Change-Id: Ib1a043b665d75fbf00cb0257b7c18e90eebab95e
2010-07-02 23:35:53 +02:00
}
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}
void vp8_optimize_mbuv(MACROBLOCK *x, const VP8_ENCODER_RTCD *rtcd)
{
int b;
ENTROPY_CONTEXT_PLANES t_above, t_left;
ENTROPY_CONTEXT *ta;
ENTROPY_CONTEXT *tl;
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if (!x->e_mbd.above_context)
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return;
if (!x->e_mbd.left_context)
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return;
vpx_memcpy(&t_above, x->e_mbd.above_context, sizeof(ENTROPY_CONTEXT_PLANES));
vpx_memcpy(&t_left, x->e_mbd.left_context, sizeof(ENTROPY_CONTEXT_PLANES));
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ta = (ENTROPY_CONTEXT *)&t_above;
tl = (ENTROPY_CONTEXT *)&t_left;
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for (b = 16; b < 24; b++)
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{
vp8_optimize_b(x, b, PLANE_TYPE_UV,
ta + vp8_block2above[b], tl + vp8_block2left[b], rtcd);
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}
}
#endif
void vp8_encode_inter16x16(const VP8_ENCODER_RTCD *rtcd, MACROBLOCK *x)
{
vp8_build_inter_predictors_mb(&x->e_mbd);
vp8_subtract_mb(rtcd, x);
vp8_transform_mb(x);
vp8_quantize_mb(x);
#if !(CONFIG_REALTIME_ONLY)
if (x->optimize)
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vp8_optimize_mb(x, rtcd);
#endif
vp8_inverse_transform_mb(IF_RTCD(&rtcd->common->idct), &x->e_mbd);
RECON_INVOKE(&rtcd->common->recon, recon_mb)
(IF_RTCD(&rtcd->common->recon), &x->e_mbd);
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}
/* this funciton is used by first pass only */
void vp8_encode_inter16x16y(const VP8_ENCODER_RTCD *rtcd, MACROBLOCK *x)
{
vp8_build_inter_predictors_mby(&x->e_mbd);
ENCODEMB_INVOKE(&rtcd->encodemb, submby)(x->src_diff, x->src.y_buffer, x->e_mbd.predictor, x->src.y_stride);
vp8_transform_mby(x);
vp8_quantize_mby(x);
vp8_inverse_transform_mby(IF_RTCD(&rtcd->common->idct), &x->e_mbd);
RECON_INVOKE(&rtcd->common->recon, recon_mby)
(IF_RTCD(&rtcd->common->recon), &x->e_mbd);
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}
void vp8_encode_inter16x16uv(const VP8_ENCODER_RTCD *rtcd, MACROBLOCK *x)
{
vp8_build_inter_predictors_mbuv(&x->e_mbd);
ENCODEMB_INVOKE(&rtcd->encodemb, submbuv)(x->src_diff, x->src.u_buffer, x->src.v_buffer, x->e_mbd.predictor, x->src.uv_stride);
vp8_transform_mbuv(x);
vp8_quantize_mbuv(x);
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vp8_inverse_transform_mbuv(IF_RTCD(&rtcd->common->idct), &x->e_mbd);
vp8_recon_intra_mbuv(IF_RTCD(&rtcd->common->recon), &x->e_mbd);
}
void vp8_encode_inter16x16uvrd(const VP8_ENCODER_RTCD *rtcd, MACROBLOCK *x)
{
vp8_build_inter_predictors_mbuv(&x->e_mbd);
ENCODEMB_INVOKE(&rtcd->encodemb, submbuv)(x->src_diff, x->src.u_buffer, x->src.v_buffer, x->e_mbd.predictor, x->src.uv_stride);
vp8_transform_mbuv(x);
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vp8_quantize_mbuv(x);
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}