2014-01-02 03:46:47 +01:00
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/*
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* Copyright (c) 2012 The WebM project authors. All Rights Reserved.
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*
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* Use of this source code is governed by a BSD-style license
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* that can be found in the LICENSE file in the root of the source
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* tree. An additional intellectual property rights grant can be found
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* in the file PATENTS. All contributing project authors may
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* be found in the AUTHORS file in the root of the source tree.
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*/
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#include <arm_neon.h>
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#include "vp8/encoder/denoising.h"
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#include "vpx_mem/vpx_mem.h"
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#include "./vp8_rtcd.h"
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/*
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* The filter function was modified to reduce the computational complexity.
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*
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* Step 1:
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* Instead of applying tap coefficients for each pixel, we calculated the
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* pixel adjustments vs. pixel diff value ahead of time.
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* adjustment = filtered_value - current_raw
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* = (filter_coefficient * diff + 128) >> 8
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* where
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* filter_coefficient = (255 << 8) / (256 + ((abs_diff * 330) >> 3));
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* filter_coefficient += filter_coefficient /
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* (3 + motion_magnitude_adjustment);
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* filter_coefficient is clamped to 0 ~ 255.
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*
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* Step 2:
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* The adjustment vs. diff curve becomes flat very quick when diff increases.
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* This allowed us to use only several levels to approximate the curve without
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* changing the filtering algorithm too much.
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* The adjustments were further corrected by checking the motion magnitude.
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* The levels used are:
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* diff level adjustment w/o adjustment w/
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* motion correction motion correction
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* [-255, -16] 3 -6 -7
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* [-15, -8] 2 -4 -5
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* [-7, -4] 1 -3 -4
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* [-3, 3] 0 diff diff
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* [4, 7] 1 3 4
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* [8, 15] 2 4 5
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* [16, 255] 3 6 7
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*/
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2014-05-14 19:55:53 +02:00
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int vp8_denoiser_filter_neon(unsigned char *mc_running_avg_y,
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int mc_running_avg_y_stride,
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unsigned char *running_avg_y,
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int running_avg_y_stride,
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unsigned char *sig, int sig_stride,
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unsigned int motion_magnitude) {
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2014-01-02 03:46:47 +01:00
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/* If motion_magnitude is small, making the denoiser more aggressive by
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* increasing the adjustment for each level, level1 adjustment is
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* increased, the deltas stay the same.
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*/
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const uint8x16_t v_level1_adjustment = vdupq_n_u8(
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(motion_magnitude <= MOTION_MAGNITUDE_THRESHOLD) ? 4 : 3);
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const uint8x16_t v_delta_level_1_and_2 = vdupq_n_u8(1);
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const uint8x16_t v_delta_level_2_and_3 = vdupq_n_u8(2);
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const uint8x16_t v_level1_threshold = vdupq_n_u8(4);
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const uint8x16_t v_level2_threshold = vdupq_n_u8(8);
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const uint8x16_t v_level3_threshold = vdupq_n_u8(16);
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2014-04-30 15:58:16 +02:00
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int64x2_t v_sum_diff_total = vdupq_n_s64(0);
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2014-01-02 03:46:47 +01:00
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/* Go over lines. */
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int i;
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for (i = 0; i < 16; ++i) {
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/* Load inputs. */
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const uint8x16_t v_sig = vld1q_u8(sig);
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const uint8x16_t v_mc_running_avg_y = vld1q_u8(mc_running_avg_y);
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/* Calculate absolute difference and sign masks. */
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const uint8x16_t v_abs_diff = vabdq_u8(v_sig, v_mc_running_avg_y);
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const uint8x16_t v_diff_pos_mask = vcltq_u8(v_sig, v_mc_running_avg_y);
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const uint8x16_t v_diff_neg_mask = vcgtq_u8(v_sig, v_mc_running_avg_y);
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/* Figure out which level that put us in. */
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const uint8x16_t v_level1_mask = vcleq_u8(v_level1_threshold,
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v_abs_diff);
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const uint8x16_t v_level2_mask = vcleq_u8(v_level2_threshold,
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v_abs_diff);
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const uint8x16_t v_level3_mask = vcleq_u8(v_level3_threshold,
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v_abs_diff);
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/* Calculate absolute adjustments for level 1, 2 and 3. */
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const uint8x16_t v_level2_adjustment = vandq_u8(v_level2_mask,
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v_delta_level_1_and_2);
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const uint8x16_t v_level3_adjustment = vandq_u8(v_level3_mask,
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v_delta_level_2_and_3);
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const uint8x16_t v_level1and2_adjustment = vaddq_u8(v_level1_adjustment,
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v_level2_adjustment);
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const uint8x16_t v_level1and2and3_adjustment = vaddq_u8(
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v_level1and2_adjustment, v_level3_adjustment);
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/* Figure adjustment absolute value by selecting between the absolute
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* difference if in level0 or the value for level 1, 2 and 3.
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*/
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const uint8x16_t v_abs_adjustment = vbslq_u8(v_level1_mask,
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v_level1and2and3_adjustment, v_abs_diff);
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/* Calculate positive and negative adjustments. Apply them to the signal
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* and accumulate them. Adjustments are less than eight and the maximum
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* sum of them (7 * 16) can fit in a signed char.
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*/
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const uint8x16_t v_pos_adjustment = vandq_u8(v_diff_pos_mask,
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v_abs_adjustment);
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const uint8x16_t v_neg_adjustment = vandq_u8(v_diff_neg_mask,
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v_abs_adjustment);
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2014-04-30 15:58:16 +02:00
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uint8x16_t v_running_avg_y = vqaddq_u8(v_sig, v_pos_adjustment);
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2014-01-02 03:46:47 +01:00
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v_running_avg_y = vqsubq_u8(v_running_avg_y, v_neg_adjustment);
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/* Store results. */
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vst1q_u8(running_avg_y, v_running_avg_y);
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/* Sum all the accumulators to have the sum of all pixel differences
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* for this macroblock.
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*/
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{
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2014-04-30 15:58:16 +02:00
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const int8x16_t v_sum_diff =
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vqsubq_s8(vreinterpretq_s8_u8(v_pos_adjustment),
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vreinterpretq_s8_u8(v_neg_adjustment));
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const int16x8_t fe_dc_ba_98_76_54_32_10 = vpaddlq_s8(v_sum_diff);
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const int32x4_t fedc_ba98_7654_3210 =
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vpaddlq_s16(fe_dc_ba_98_76_54_32_10);
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const int64x2_t fedcba98_76543210 =
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vpaddlq_s32(fedc_ba98_7654_3210);
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v_sum_diff_total = vqaddq_s64(v_sum_diff_total, fedcba98_76543210);
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2014-01-02 03:46:47 +01:00
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}
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/* Update pointers for next iteration. */
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sig += sig_stride;
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mc_running_avg_y += mc_running_avg_y_stride;
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running_avg_y += running_avg_y_stride;
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}
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/* Too much adjustments => copy block. */
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2014-04-30 15:58:16 +02:00
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{
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const int64x1_t x = vqadd_s64(vget_high_s64(v_sum_diff_total),
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vget_low_s64(v_sum_diff_total));
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const int s0 = vget_lane_s32(vabs_s32(vreinterpret_s32_s64(x)), 0);
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if (s0 > SUM_DIFF_THRESHOLD)
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return COPY_BLOCK;
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}
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2014-01-02 03:46:47 +01:00
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/* Tell above level that block was filtered. */
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2014-04-30 15:58:16 +02:00
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running_avg_y -= running_avg_y_stride * 16;
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sig -= sig_stride * 16;
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vp8_copy_mem16x16(running_avg_y, running_avg_y_stride, sig, sig_stride);
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2014-01-02 03:46:47 +01:00
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return FILTER_BLOCK;
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}
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