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185 lines
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C++

#pragma once
#include <vector>
#include <opencv2/opencv.hpp> // all opencv header
#include <cmath>
#include "hdrplus/burst.h"
#define TILE_SIZE 16
#define TEMPORAL_FACTOR 75
#define SPATIAL_FACTOR 0.1
namespace hdrplus
{
class merge
{
public:
int offset = TILE_SIZE / 2;
float baseline_lambda_shot = 3.24 * pow( 10, -4 );
float baseline_lambda_read = 4.3 * pow( 10, -6 );
merge() = default;
~merge() = default;
/**
* @brief Run alignment on burst of images
*
* @param burst_images collection of burst images
* @param alignments alignment in pixel value pair.
* Outer most vector is per alternative image.
* Inner most two vector is for horizontal & vertical tiles
*/
void process( hdrplus::burst& burst_images, \
std::vector<std::vector<std::vector<std::pair<int, int>>>>& alignments);
/*
std::vector<cv::Mat> get_other_tiles(); //return the other tile list T_1 to T_n
std::vector<cv::Mat> vector_math(string operation, reference_tile, other_tile_list); //for loop allowing operations across single element and list
std::vector<cv::Mat> scalar_vector_math(string operation, scalar num, std::vector<cv::Mat> tile_list); //for loop allowing operations across single element and list
std::vector<cv::Mat> average_vector(std::vector<cv::Mat> tile_list); //take average of vector elements
*/
private:
float tileRMS(cv::Mat tile) {
cv::Mat squared;
cv::multiply(tile, tile, squared);
return sqrt(cv::mean(squared)[0]);
}
std::vector<float> getNoiseVariance(std::vector<cv::Mat> tiles, float lambda_shot, float lambda_read) {
std::vector<float> noise_variance;
for (auto tile : tiles) {
noise_variance.push_back(lambda_shot * tileRMS(tile) + lambda_read);
}
return noise_variance;
}
cv::Mat cosineWindow1D(cv::Mat input, int window_size = TILE_SIZE) {
cv::Mat output = input.clone();
for (int i = 0; i < input.cols; ++i) {
output.at<float>(0, i) = 1. / 2. - 1. / 2. * cos(2 * M_PI * (input.at<float>(0, i) + 1 / 2.) / window_size);
}
return output;
}
cv::Mat cosineWindow2D(cv::Mat tile) {
int window_size = tile.rows; // Assuming square tile
cv::Mat output_tile = tile.clone();
cv::Mat window = cv::Mat::zeros(1, window_size, CV_32F);
for(int i = 0; i < window_size; ++i) {
window.at<float>(i) = i;
}
cv::Mat window_x = cosineWindow1D(window, window_size);
window_x = cv::repeat(window_x, window_size, 1);
cv::Mat window_2d = window_x.mul(window_x.t());
cv::Mat window_applied;
cv::multiply(tile, window_2d, window_applied, 1, CV_32F);
return window_applied;
}
cv::Mat cat2Dtiles(std::vector<std::vector<cv::Mat>> tiles) {
std::vector<cv::Mat> rows;
for (auto row_tiles : tiles) {
cv::Mat row;
cv::hconcat(row_tiles, row);
rows.push_back(row);
}
cv::Mat img;
cv::vconcat(rows, img);
return img;
}
void circshift(cv::Mat &out, const cv::Point &delta)
{
cv::Size sz = out.size();
// error checking
assert(sz.height > 0 && sz.width > 0);
// no need to shift
if ((sz.height == 1 && sz.width == 1) || (delta.x == 0 && delta.y == 0))
return;
// delta transform
int x = delta.x;
int y = delta.y;
if (x > 0) x = x % sz.width;
if (y > 0) y = y % sz.height;
if (x < 0) x = x % sz.width + sz.width;
if (y < 0) y = y % sz.height + sz.height;
// in case of multiple dimensions
std::vector<cv::Mat> planes;
split(out, planes);
for (size_t i = 0; i < planes.size(); i++)
{
// vertical
cv::Mat tmp0, tmp1, tmp2, tmp3;
cv::Mat q0(planes[i], cv::Rect(0, 0, sz.width, sz.height - y));
cv::Mat q1(planes[i], cv::Rect(0, sz.height - y, sz.width, y));
q0.copyTo(tmp0);
q1.copyTo(tmp1);
tmp0.copyTo(planes[i](cv::Rect(0, y, sz.width, sz.height - y)));
tmp1.copyTo(planes[i](cv::Rect(0, 0, sz.width, y)));
// horizontal
cv::Mat q2(planes[i], cv::Rect(0, 0, sz.width - x, sz.height));
cv::Mat q3(planes[i], cv::Rect(sz.width - x, 0, x, sz.height));
q2.copyTo(tmp2);
q3.copyTo(tmp3);
tmp2.copyTo(planes[i](cv::Rect(x, 0, sz.width - x, sz.height)));
tmp3.copyTo(planes[i](cv::Rect(0, 0, x, sz.height)));
}
cv::merge(planes, out);
}
void fftshift(cv::Mat &out)
{
cv::Size sz = out.size();
cv::Point pt(0, 0);
pt.x = (int) floor(sz.width / 2.0);
pt.y = (int) floor(sz.height / 2.0);
circshift(out, pt);
}
void ifftshift(cv::Mat &out)
{
cv::Size sz = out.size();
cv::Point pt(0, 0);
pt.x = (int) ceil(sz.width / 2.0);
pt.y = (int) ceil(sz.height / 2.0);
circshift(out, pt);
}
std::vector<cv::Mat> getReferenceTiles(cv::Mat reference_image);
cv::Mat mergeTiles(std::vector<cv::Mat> tiles, int rows, int cols);
cv::Mat processChannel( hdrplus::burst& burst_images, \
std::vector<std::vector<std::vector<std::pair<int, int>>>>& alignments, \
cv::Mat channel_image, \
std::vector<cv::Mat> alternate_channel_i_list,\
float lambda_shot, \
float lambda_read);
//temporal denoise
std::vector<cv::Mat> temporal_denoise(std::vector<cv::Mat> tiles, std::vector<std::vector<cv::Mat>> alt_tiles, std::vector<float> noise_variance, float temporal_factor);
std::vector<cv::Mat> spatial_denoise(std::vector<cv::Mat> tiles, int num_alts, std::vector<float> noise_variance, float spatial_factor);
};
} // namespace hdrplus