f9a961c5d0
These are in response to a post-commit review in Ib6664df44090e8cfa4db9f2f9e0556931ccfe5c8 Change-Id: I1e07ccab18558dfdd996547a72a396abe02ed23d
211 lines
8.7 KiB
C
211 lines
8.7 KiB
C
/*
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* Copyright (c) 2016 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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