f883b42cab
Cherry-Picked the following commits: 0defd8f Changed "WebM" to "AOMedia" & "webm" to "aomedia" 54e6676 Replace "VPx" by "AVx" 5082a36 Change "Vpx" to "Avx" 7df44f1 Replace "Vp9" w/ "Av1" 967f722 Remove kVp9CodecId 828f30c Change "Vp8" to "AOM" 030b5ff AUTHORS regenerated 2524cae Add ref-mv experimental flag 016762b Change copyright notice to AOMedia form 81e5526 Replace vp9 w/ av1 9b94565 Add missing files fa8ca9f Change "vp9" to "av1" ec838b7 Convert "vp8" to "aom" 80edfa0 Change "VP9" to "AV1" d1a11fb Change "vp8" to "aom" 7b58251 Point to WebM test data dd1a5c8 Replace "VP8" with "AOM" ff00fc0 Change "VPX" to "AOM" 01dee0b Change "vp10" to "av1" in source code cebe6f0 Convert "vpx" to "aom" 17b0567 rename vp10*.mk to av1_*.mk fe5f8a8 rename files vp10_* to av1_* Change-Id: I6fc3d18eb11fc171e46140c836ad5339cf6c9419
211 lines
8.7 KiB
C
211 lines
8.7 KiB
C
/*
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* Copyright (c) 2010 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 <stdio.h>
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#include <stdlib.h>
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#include <memory.h>
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#include <math.h>
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#include "av1/encoder/corner_match.h"
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#define MATCH_SZ 15
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#define MATCH_SZ_BY2 ((MATCH_SZ - 1) / 2)
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#define MATCH_SZ_SQ (MATCH_SZ * MATCH_SZ)
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#define SEARCH_SZ 9
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#define SEARCH_SZ_BY2 ((SEARCH_SZ - 1) / 2)
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#define THRESHOLD_NCC 0.80
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static double compute_variance(unsigned char *im, int stride, int x, int y,
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double *mean) {
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double sum = 0.0;
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double sumsq = 0.0;
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double var;
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int i, j;
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for (i = 0; i < MATCH_SZ; ++i)
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for (j = 0; j < MATCH_SZ; ++j) {
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sum += im[(i + y - MATCH_SZ_BY2) * stride + (j + x - MATCH_SZ_BY2)];
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sumsq += im[(i + y - MATCH_SZ_BY2) * stride + (j + x - MATCH_SZ_BY2)] *
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im[(i + y - MATCH_SZ_BY2) * stride + (j + x - MATCH_SZ_BY2)];
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}
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var = (sumsq * MATCH_SZ_SQ - sum * sum) / (MATCH_SZ_SQ * MATCH_SZ_SQ);
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if (mean) *mean = sum / MATCH_SZ_SQ;
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return var;
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}
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static double compute_cross_correlation(unsigned char *im1, int stride1, int x1,
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int y1, unsigned char *im2, int stride2,
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int x2, int y2) {
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double sum1 = 0;
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double sum2 = 0;
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double cross = 0;
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double corr;
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int i, j;
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for (i = 0; i < MATCH_SZ; ++i)
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for (j = 0; j < MATCH_SZ; ++j) {
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sum1 += im1[(i + y1 - MATCH_SZ_BY2) * stride1 + (j + x1 - MATCH_SZ_BY2)];
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sum2 += im2[(i + y2 - MATCH_SZ_BY2) * stride2 + (j + x2 - MATCH_SZ_BY2)];
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cross +=
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im1[(i + y1 - MATCH_SZ_BY2) * stride1 + (j + x1 - MATCH_SZ_BY2)] *
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im2[(i + y2 - MATCH_SZ_BY2) * stride2 + (j + x2 - MATCH_SZ_BY2)];
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}
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corr = (cross * MATCH_SZ_SQ - sum1 * sum2) / (MATCH_SZ_SQ * MATCH_SZ_SQ);
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return corr;
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}
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static int is_eligible_point(double pointx, double pointy, int width,
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int height) {
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return (pointx >= MATCH_SZ_BY2 && pointy >= MATCH_SZ_BY2 &&
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pointx + MATCH_SZ_BY2 < width && pointy + MATCH_SZ_BY2 < height);
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}
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static int is_eligible_distance(double point1x, double point1y, double point2x,
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double point2y, int width, int height) {
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const int thresh = (width < height ? height : width) >> 4;
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return ((point1x - point2x) * (point1x - point2x) +
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(point1y - point2y) * (point1y - point2y)) <= thresh * thresh;
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}
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static void improve_correspondence(unsigned char *frm, unsigned char *ref,
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int width, int height, int frm_stride,
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int ref_stride,
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correspondence *correspondences,
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int num_correspondences) {
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int i;
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for (i = 0; i < num_correspondences; ++i) {
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double template_norm =
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compute_variance(frm, frm_stride, (int)correspondences[i].x,
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(int)correspondences[i].y, NULL);
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int x, y, best_x = 0, best_y = 0;
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double best_match_ncc = 0.0;
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for (y = -SEARCH_SZ_BY2; y <= SEARCH_SZ_BY2; ++y) {
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for (x = -SEARCH_SZ_BY2; x <= SEARCH_SZ_BY2; ++x) {
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double match_ncc;
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double subimage_norm;
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if (!is_eligible_point((int)correspondences[i].rx + x,
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(int)correspondences[i].ry + y, width, height))
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continue;
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if (!is_eligible_distance(
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(int)correspondences[i].x, (int)correspondences[i].y,
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(int)correspondences[i].rx + x, (int)correspondences[i].ry + y,
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width, height))
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continue;
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subimage_norm =
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compute_variance(ref, ref_stride, (int)correspondences[i].rx + x,
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(int)correspondences[i].ry + y, NULL);
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match_ncc = compute_cross_correlation(
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frm, frm_stride, (int)correspondences[i].x,
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(int)correspondences[i].y, ref, ref_stride,
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(int)correspondences[i].rx + x,
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(int)correspondences[i].ry + y) /
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sqrt(template_norm * subimage_norm);
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if (match_ncc > best_match_ncc) {
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best_match_ncc = match_ncc;
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best_y = y;
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best_x = x;
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}
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}
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}
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correspondences[i].rx += (double)best_x;
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correspondences[i].ry += (double)best_y;
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}
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for (i = 0; i < num_correspondences; ++i) {
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double template_norm =
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compute_variance(ref, ref_stride, (int)correspondences[i].rx,
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(int)correspondences[i].ry, NULL);
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int x, y, best_x = 0, best_y = 0;
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double best_match_ncc = 0.0;
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for (y = -SEARCH_SZ_BY2; y <= SEARCH_SZ_BY2; ++y)
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for (x = -SEARCH_SZ_BY2; x <= SEARCH_SZ_BY2; ++x) {
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double match_ncc;
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double subimage_norm;
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if (!is_eligible_point((int)correspondences[i].x + x,
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(int)correspondences[i].y + y, width, height))
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continue;
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if (!is_eligible_distance((int)correspondences[i].x + x,
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(int)correspondences[i].y + y,
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(int)correspondences[i].rx,
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(int)correspondences[i].ry, width, height))
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continue;
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subimage_norm =
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compute_variance(frm, frm_stride, (int)correspondences[i].x + x,
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(int)correspondences[i].y + y, NULL);
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match_ncc =
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compute_cross_correlation(
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frm, frm_stride, (int)correspondences[i].x + x,
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(int)correspondences[i].y + y, ref, ref_stride,
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(int)correspondences[i].rx, (int)correspondences[i].ry) /
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sqrt(template_norm * subimage_norm);
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if (match_ncc > best_match_ncc) {
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best_match_ncc = match_ncc;
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best_y = y;
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best_x = x;
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}
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}
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correspondences[i].x += best_x;
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correspondences[i].y += best_y;
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}
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}
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int determine_correspondence(unsigned char *frm, int *frm_corners,
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int num_frm_corners, unsigned char *ref,
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int *ref_corners, int num_ref_corners, int width,
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int height, int frm_stride, int ref_stride,
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double *correspondence_pts) {
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// TODO(sarahparker) Improve this to include 2-way match
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int i, j;
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correspondence *correspondences = (correspondence *)correspondence_pts;
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int num_correspondences = 0;
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for (i = 0; i < num_frm_corners; ++i) {
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double best_match_ncc = 0.0;
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double template_norm;
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int best_match_j = -1;
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if (!is_eligible_point(frm_corners[2 * i], frm_corners[2 * i + 1], width,
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height))
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continue;
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template_norm = compute_variance(frm, frm_stride, frm_corners[2 * i],
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frm_corners[2 * i + 1], NULL);
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for (j = 0; j < num_ref_corners; ++j) {
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double match_ncc;
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double subimage_norm;
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if (!is_eligible_point(ref_corners[2 * j], ref_corners[2 * j + 1], width,
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height))
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continue;
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if (!is_eligible_distance(frm_corners[2 * i], frm_corners[2 * i + 1],
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ref_corners[2 * j], ref_corners[2 * j + 1],
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width, height))
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continue;
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subimage_norm = compute_variance(ref, ref_stride, ref_corners[2 * j],
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ref_corners[2 * j + 1], NULL);
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match_ncc = compute_cross_correlation(frm, frm_stride, frm_corners[2 * i],
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frm_corners[2 * i + 1], ref,
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ref_stride, ref_corners[2 * j],
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ref_corners[2 * j + 1]) /
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sqrt(template_norm * subimage_norm);
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if (match_ncc > best_match_ncc) {
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best_match_ncc = match_ncc;
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best_match_j = j;
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}
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}
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if (best_match_ncc > THRESHOLD_NCC) {
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correspondences[num_correspondences].x = (double)frm_corners[2 * i];
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correspondences[num_correspondences].y = (double)frm_corners[2 * i + 1];
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correspondences[num_correspondences].rx =
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(double)ref_corners[2 * best_match_j];
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correspondences[num_correspondences].ry =
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(double)ref_corners[2 * best_match_j + 1];
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num_correspondences++;
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}
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}
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improve_correspondence(frm, ref, width, height, frm_stride, ref_stride,
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correspondences, num_correspondences);
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return num_correspondences;
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}
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