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/*
* Copyright (c) 2016, Alliance for Open Media. All rights reserved
*
* This source code is subject to the terms of the BSD 2 Clause License and
* the Alliance for Open Media Patent License 1.0. If the BSD 2 Clause License
* was not distributed with this source code in the LICENSE file, you can
* obtain it at www.aomedia.org/license/software. If the Alliance for Open
* Media Patent License 1.0 was not distributed with this source code in the
* PATENTS file, you can obtain it at www.aomedia.org/license/patent.
*/
#include <stdlib.h>
#include <memory.h>
#include <math.h>
#include "config/av1_rtcd.h"
#include "av1/encoder/corner_match.h"
#define SEARCH_SZ 9
#define SEARCH_SZ_BY2 ((SEARCH_SZ - 1) / 2)
#define THRESHOLD_NCC 0.75
/* Compute var(im) * MATCH_SZ_SQ over a MATCH_SZ by MATCH_SZ window of im,
centered at (x, y).
*/
static double compute_variance(unsigned char *im, int stride, int x, int y) {
int sum = 0;
int sumsq = 0;
int 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;
return (double)var;
}
/* Compute corr(im1, im2) * MATCH_SZ * stddev(im1), where the
correlation/standard deviation are taken over MATCH_SZ by MATCH_SZ windows
of each image, centered at (x1, y1) and (x2, y2) respectively.
*/
double compute_cross_correlation_c(unsigned char *im1, int stride1, int x1,
int y1, unsigned char *im2, int stride2,
int x2, int y2) {
int v1, v2;
int sum1 = 0;
int sum2 = 0;
int sumsq2 = 0;
int cross = 0;
int var2, cov;
int i, j;
for (i = 0; i < MATCH_SZ; ++i)
for (j = 0; j < MATCH_SZ; ++j) {
v1 = im1[(i + y1 - MATCH_SZ_BY2) * stride1 + (j + x1 - MATCH_SZ_BY2)];
v2 = im2[(i + y2 - MATCH_SZ_BY2) * stride2 + (j + x2 - MATCH_SZ_BY2)];
sum1 += v1;
sum2 += v2;
sumsq2 += v2 * v2;
cross += v1 * v2;
}
var2 = sumsq2 * MATCH_SZ_SQ - sum2 * sum2;
cov = cross * MATCH_SZ_SQ - sum1 * sum2;
return cov / sqrt((double)var2);
}
static int is_eligible_point(int pointx, int 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(int point1x, int point1y, int point2x,
int 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) {
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;
if (!is_eligible_point(correspondences[i].rx + x,
correspondences[i].ry + y, width, height))
continue;
if (!is_eligible_distance(correspondences[i].x, correspondences[i].y,
correspondences[i].rx + x,
correspondences[i].ry + y, width, height))
continue;
match_ncc = compute_cross_correlation(
frm, frm_stride, correspondences[i].x, correspondences[i].y, ref,
ref_stride, correspondences[i].rx + x, correspondences[i].ry + y);
if (match_ncc > best_match_ncc) {
best_match_ncc = match_ncc;
best_y = y;
best_x = x;
}
}
}
correspondences[i].rx += best_x;
correspondences[i].ry += best_y;
}
for (i = 0; i < num_correspondences; ++i) {
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;
if (!is_eligible_point(correspondences[i].x + x,
correspondences[i].y + y, width, height))
continue;
if (!is_eligible_distance(
correspondences[i].x + x, correspondences[i].y + y,
correspondences[i].rx, correspondences[i].ry, width, height))
continue;
match_ncc = compute_cross_correlation(
ref, ref_stride, correspondences[i].rx, correspondences[i].ry, frm,
frm_stride, correspondences[i].x + x, correspondences[i].y + y);
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,
int *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;
for (j = 0; j < num_ref_corners; ++j) {
double match_ncc;
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;
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]);
if (match_ncc > best_match_ncc) {
best_match_ncc = match_ncc;
best_match_j = j;
}
}
// Note: We want to test if the best correlation is >= THRESHOLD_NCC,
// but need to account for the normalization in compute_cross_correlation.
template_norm = compute_variance(frm, frm_stride, frm_corners[2 * i],
frm_corners[2 * i + 1]);
if (best_match_ncc > THRESHOLD_NCC * sqrt(template_norm)) {
correspondences[num_correspondences].x = frm_corners[2 * i];
correspondences[num_correspondences].y = frm_corners[2 * i + 1];
correspondences[num_correspondences].rx = ref_corners[2 * best_match_j];
correspondences[num_correspondences].ry =
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;
}
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