align : image pyramid

main
Xiao Song 3 years ago
parent e1112eac5f
commit 01881ca089

@ -25,6 +25,7 @@ class align
void process( const hdrplus::burst& burst_images, \
std::vector<std::vector<std::vector<std::pair<int, int>>>>& aligements );
private:
const std::vector<int> inv_scale_factors = { 1, 2, 2, 4 };
};

@ -119,6 +119,4 @@ cv::Mat downsample_nearest_neighbour( cv::Mat src_image )
return dst_image;
}
cv::Mat gaussian_blur( cv::Mat src_image, double sigma );
} // namespace hdrplus

@ -1,4 +1,6 @@
#include <vector>
#include <string>
#include <stdexcept> // std::runtime_error
#include <opencv2/opencv.hpp> // all opencv header
#include "hdrplus/align.h"
#include "hdrplus/burst.h"
@ -7,46 +9,63 @@
namespace hdrplus
{
// static function only visible within file
static void build_image_pyramid( \
std::vector<cv::Mat>& images_pyramid, \
const cv::Mat& src_image, \
const std::vector<int>& inv_scale_factors )
{
images_pyramid.resize( inv_scale_factors.size() );
for ( int i = 0; i < inv_scale_factors.size(); ++i )
{
cv::Mat blur_image;
cv::Mat downsample_image;
switch ( inv_scale_factors[ i ] )
{
case 1:
images_pyramid[ images_pyramid.size() - i - 1 ] = src_image;
// cv::Mat use reference count, will not create deep copy
downsample_image = src_image;
break;
case 2:
// Gaussian blur
cv::GaussianBlur( downsample_image, blur_image, cv::Size(0, 0), 1.0 );
// Downsample
downsample_image = downsample_nearest_neighbour<uint16_t, 2>( blur_image );
// Add
images_pyramid[ images_pyramid.size() - i - 1 ] = downsample_image;
break;
case 4:
cv::GaussianBlur( downsample_image, blur_image, cv::Size(0, 0), 2.0 );
downsample_image = downsample_nearest_neighbour<uint16_t, 4>( blur_image );
images_pyramid[ images_pyramid.size() - i - 1 ] = downsample_image;
break;
default:
throw std::runtime_error("inv scale factor " + std::to_string( inv_scale_factors[ i ]) + "invalid" );
}
}
}
void align::process( const hdrplus::burst& burst_images, \
std::vector<std::vector<std::vector<std::pair<int, int>>>>& aligements )
{
/*
// Build image pyramid
std::vector<std::vector<cv::Mat>> grayscale_images_pyramid;
grayscale_images_pyramid.resize( burst_images.grayscale_images_pad.size() );
for ( int img_idx = 0; img_idx < burst_images.grayscale_images_pad.size(); ++img_idx )
{
grayscale_images_pyramid[ img_idx ].resize( inv_scale_factors.size() );
// pyramid image are laied out from coarse to fine
// level 0 is the original grayscale image
grayscale_images_pyramid[ img_idx ][ inv_scale_factors.size() - 1 ] = burst_images.grayscale_images_pad[ img_idx];
// downsample and gaussian blur
for ( int i = 1; i < inv_scale_factors.size(); ++i )
{
int inv_scale_factor_i = inv_scale_factors[ i ];
cv::Mat blurred_image = \
hdrplus::gaussian_blur( grayscale_images_pyramid[ img_idx ][ i - 1 ], inv_scale_factor_i * 0.5 );
// Get around with template
cv::Mat downsampled_blurred_image;
if ( inv_scale_factor_i == 2 )
{
hdrplus::downsample_nearest_neighbour<uint16_t, 2>( blurred_image );
}
else if ( inv_scale_factor_i == 4 )
{
hdrplus::downsample_nearest_neighbour<uint16_t, 4>( blurred_image );
build_image_pyramid( grayscale_images_pyramid[ img_idx ], \
burst_images.grayscale_images_pad[ img_idx ], \
inv_scale_factors );
}
grayscale_images_pyramid[ img_idx ][ inv_scale_factors.size() - i - 1 ] = downsampled_blurred_image;
}
}
cv::GaussianBlur( src_image, dst_image, cv::Size(0, 0), sigma );
*/
}
} // namespace hdrplus

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