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// This sample shows the difference of adaptive bilateral filter and bilateral filter.
#include "opencv2/core/core.hpp"
#include "opencv2/imgproc/imgproc.hpp"
#include "opencv2/highgui/highgui.hpp"
#include "opencv2/ocl/ocl.hpp"
using namespace cv;
using namespace std;
int main( int argc, const char** argv )
{
const char* keys =
"{ i | input | | specify input image }"
"{ k | ksize | 11 | specify kernel size }"
"{ s | sSpace | 3 | specify sigma space }"
"{ c | sColor | 30 | specify max color }"
"{ h | help | false | print help message }";
CommandLineParser cmd(argc, argv, keys);
if (cmd.get<bool>("help"))
{
cout << "Usage : adaptive_bilateral_filter [options]" << endl;
cout << "Available options:" << endl;
cmd.printParams();
return EXIT_SUCCESS;
}
string src_path = cmd.get<string>("i");
int ks = cmd.get<int>("k");
const char * winName[] = {"input", "ABF OpenCL", "BF OpenCL"};
Mat src = imread(src_path);
if (src.empty())
{
cout << "error read image: " << src_path << endl;
return EXIT_FAILURE;
}
double sigmaSpace = cmd.get<int>("s");
// sigma for checking pixel values. This is used as is in the "normal" bilateral filter,
// and it is used as an upper clamp on the adaptive case.
double sigmacolor = cmd.get<int>("c");
ocl::oclMat dsrc(src), dABFilter, dBFilter;
Size ksize(ks, ks);
// ksize is the total width/height of neighborhood used to calculate local variance.
// sigmaSpace is not a priori related to ksize/2.
ocl::adaptiveBilateralFilter(dsrc, dABFilter, ksize, sigmaSpace, sigmacolor);
ocl::bilateralFilter(dsrc, dBFilter, ks, sigmacolor, sigmaSpace);
Mat abFilter = dABFilter, bFilter = dBFilter;
ocl::finish();
imshow(winName[0], src);
imshow(winName[1], abFilter);
imshow(winName[2], bFilter);
waitKey();
return EXIT_SUCCESS;
}
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