| /* |
| * Copyright (c) 2010 The WebM project authors. All Rights Reserved. |
| * |
| * 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. |
| */ |
| |
| #include <stdio.h> |
| #include <stdlib.h> |
| #include <memory.h> |
| #include <math.h> |
| |
| #include "vp10/encoder/corner_match.h" |
| |
| #define MATCH_SZ 15 |
| #define MATCH_SZ_BY2 ((MATCH_SZ - 1) / 2) |
| #define MATCH_SZ_SQ (MATCH_SZ * MATCH_SZ) |
| #define SEARCH_SZ 9 |
| #define SEARCH_SZ_BY2 ((SEARCH_SZ - 1) / 2) |
| |
| #define THRESHOLD_NCC 0.80 |
| |
| static double compute_variance(unsigned char *im, int stride, int x, int y, |
| double *mean) { |
| double sum = 0.0; |
| double sumsq = 0.0; |
| double var; |
| int i, j; |
| for (i = 0; i < MATCH_SZ; ++i) |
| for (j = 0; j < MATCH_SZ; ++j) { |
| sum += im[(i + y - MATCH_SZ_BY2) * stride + (j + x - MATCH_SZ_BY2)]; |
| sumsq += im[(i + y - MATCH_SZ_BY2) * stride + (j + x - MATCH_SZ_BY2)] * |
| im[(i + y - MATCH_SZ_BY2) * stride + (j + x - MATCH_SZ_BY2)]; |
| } |
| var = (sumsq * MATCH_SZ_SQ - sum * sum) / (MATCH_SZ_SQ * MATCH_SZ_SQ); |
| if (mean) *mean = sum / MATCH_SZ_SQ; |
| return var; |
| } |
| |
| static double compute_cross_correlation(unsigned char *im1, int stride1, int x1, |
| int y1, unsigned char *im2, int stride2, |
| int x2, int y2) { |
| double sum1 = 0; |
| double sum2 = 0; |
| double cross = 0; |
| double corr; |
| int i, j; |
| for (i = 0; i < MATCH_SZ; ++i) |
| for (j = 0; j < MATCH_SZ; ++j) { |
| sum1 += im1[(i + y1 - MATCH_SZ_BY2) * stride1 + (j + x1 - MATCH_SZ_BY2)]; |
| sum2 += im2[(i + y2 - MATCH_SZ_BY2) * stride2 + (j + x2 - MATCH_SZ_BY2)]; |
| cross += |
| im1[(i + y1 - MATCH_SZ_BY2) * stride1 + (j + x1 - MATCH_SZ_BY2)] * |
| im2[(i + y2 - MATCH_SZ_BY2) * stride2 + (j + x2 - MATCH_SZ_BY2)]; |
| } |
| corr = (cross * MATCH_SZ_SQ - sum1 * sum2) / (MATCH_SZ_SQ * MATCH_SZ_SQ); |
| return corr; |
| } |
| |
| static int is_eligible_point(double pointx, double pointy, int width, |
| int height) { |
| return (pointx >= MATCH_SZ_BY2 && pointy >= MATCH_SZ_BY2 && |
| pointx + MATCH_SZ_BY2 < width && pointy + MATCH_SZ_BY2 < height); |
| } |
| |
| static int is_eligible_distance(double point1x, double point1y, double point2x, |
| double point2y, int width, int height) { |
| const int thresh = (width < height ? height : width) >> 4; |
| return ((point1x - point2x) * (point1x - point2x) + |
| (point1y - point2y) * (point1y - point2y)) <= thresh * thresh; |
| } |
| |
| static void improve_correspondence(unsigned char *frm, unsigned char *ref, |
| int width, int height, int frm_stride, |
| int ref_stride, |
| correspondence *correspondences, |
| int num_correspondences) { |
| int i; |
| for (i = 0; i < num_correspondences; ++i) { |
| double template_norm = |
| compute_variance(frm, frm_stride, (int)correspondences[i].x, |
| (int)correspondences[i].y, NULL); |
| int x, y, best_x = 0, best_y = 0; |
| double best_match_ncc = 0.0; |
| for (y = -SEARCH_SZ_BY2; y <= SEARCH_SZ_BY2; ++y) { |
| for (x = -SEARCH_SZ_BY2; x <= SEARCH_SZ_BY2; ++x) { |
| double match_ncc; |
| double subimage_norm; |
| if (!is_eligible_point((int)correspondences[i].rx + x, |
| (int)correspondences[i].ry + y, width, height)) |
| continue; |
| if (!is_eligible_distance( |
| (int)correspondences[i].x, (int)correspondences[i].y, |
| (int)correspondences[i].rx + x, (int)correspondences[i].ry + y, |
| width, height)) |
| continue; |
| subimage_norm = |
| compute_variance(ref, ref_stride, (int)correspondences[i].rx + x, |
| (int)correspondences[i].ry + y, NULL); |
| match_ncc = compute_cross_correlation( |
| frm, frm_stride, (int)correspondences[i].x, |
| (int)correspondences[i].y, ref, ref_stride, |
| (int)correspondences[i].rx + x, |
| (int)correspondences[i].ry + y) / |
| sqrt(template_norm * subimage_norm); |
| if (match_ncc > best_match_ncc) { |
| best_match_ncc = match_ncc; |
| best_y = y; |
| best_x = x; |
| } |
| } |
| } |
| correspondences[i].rx += (double)best_x; |
| correspondences[i].ry += (double)best_y; |
| } |
| for (i = 0; i < num_correspondences; ++i) { |
| double template_norm = |
| compute_variance(ref, ref_stride, (int)correspondences[i].rx, |
| (int)correspondences[i].ry, NULL); |
| int x, y, best_x = 0, best_y = 0; |
| double best_match_ncc = 0.0; |
| for (y = -SEARCH_SZ_BY2; y <= SEARCH_SZ_BY2; ++y) |
| for (x = -SEARCH_SZ_BY2; x <= SEARCH_SZ_BY2; ++x) { |
| double match_ncc; |
| double subimage_norm; |
| if (!is_eligible_point((int)correspondences[i].x + x, |
| (int)correspondences[i].y + y, width, height)) |
| continue; |
| if (!is_eligible_distance((int)correspondences[i].x + x, |
| (int)correspondences[i].y + y, |
| (int)correspondences[i].rx, |
| (int)correspondences[i].ry, width, height)) |
| continue; |
| subimage_norm = |
| compute_variance(frm, frm_stride, (int)correspondences[i].x + x, |
| (int)correspondences[i].y + y, NULL); |
| match_ncc = |
| compute_cross_correlation( |
| frm, frm_stride, (int)correspondences[i].x + x, |
| (int)correspondences[i].y + y, ref, ref_stride, |
| (int)correspondences[i].rx, (int)correspondences[i].ry) / |
| sqrt(template_norm * subimage_norm); |
| if (match_ncc > best_match_ncc) { |
| best_match_ncc = match_ncc; |
| best_y = y; |
| best_x = x; |
| } |
| } |
| correspondences[i].x += best_x; |
| correspondences[i].y += best_y; |
| } |
| } |
| |
| int determine_correspondence(unsigned char *frm, int *frm_corners, |
| int num_frm_corners, unsigned char *ref, |
| int *ref_corners, int num_ref_corners, int width, |
| int height, int frm_stride, int ref_stride, |
| double *correspondence_pts) { |
| // TODO(sarahparker) Improve this to include 2-way match |
| int i, j; |
| correspondence *correspondences = (correspondence *)correspondence_pts; |
| int num_correspondences = 0; |
| for (i = 0; i < num_frm_corners; ++i) { |
| double best_match_ncc = 0.0; |
| double template_norm; |
| int best_match_j = -1; |
| if (!is_eligible_point(frm_corners[2 * i], frm_corners[2 * i + 1], width, |
| height)) |
| continue; |
| template_norm = compute_variance(frm, frm_stride, frm_corners[2 * i], |
| frm_corners[2 * i + 1], NULL); |
| for (j = 0; j < num_ref_corners; ++j) { |
| double match_ncc; |
| double subimage_norm; |
| if (!is_eligible_point(ref_corners[2 * j], ref_corners[2 * j + 1], width, |
| height)) |
| continue; |
| if (!is_eligible_distance(frm_corners[2 * i], frm_corners[2 * i + 1], |
| ref_corners[2 * j], ref_corners[2 * j + 1], |
| width, height)) |
| continue; |
| subimage_norm = compute_variance(ref, ref_stride, ref_corners[2 * j], |
| ref_corners[2 * j + 1], NULL); |
| match_ncc = compute_cross_correlation(frm, frm_stride, frm_corners[2 * i], |
| frm_corners[2 * i + 1], ref, |
| ref_stride, ref_corners[2 * j], |
| ref_corners[2 * j + 1]) / |
| sqrt(template_norm * subimage_norm); |
| if (match_ncc > best_match_ncc) { |
| best_match_ncc = match_ncc; |
| best_match_j = j; |
| } |
| } |
| if (best_match_ncc > THRESHOLD_NCC) { |
| correspondences[num_correspondences].x = (double)frm_corners[2 * i]; |
| correspondences[num_correspondences].y = (double)frm_corners[2 * i + 1]; |
| correspondences[num_correspondences].rx = |
| (double)ref_corners[2 * best_match_j]; |
| correspondences[num_correspondences].ry = |
| (double)ref_corners[2 * best_match_j + 1]; |
| num_correspondences++; |
| } |
| } |
| improve_correspondence(frm, ref, width, height, frm_stride, ref_stride, |
| correspondences, num_correspondences); |
| return num_correspondences; |
| } |
