Commit 7297f022 authored by Vadim Pisarevsky's avatar Vadim Pisarevsky

added optimized anisotropic diffusion filter (rewrite of…

added optimized anisotropic diffusion filter (rewrite of https://github.com/opencv/opencv/pull/8362)
parent 5e4d9b0b
......@@ -122,6 +122,27 @@ The function transforms a binary blob image into a skeletized form using the tec
*/
CV_EXPORTS_W void thinning( InputArray src, OutputArray dst, int thinningType = THINNING_ZHANGSUEN);
/** @brief Performs anisotropic diffusian on an image.
The function applies Perona-Malik anisotropic diffusion to an image. This is the solution to the partial differential equation:
\f[{\frac {\partial I}{\partial t}}={\mathrm {div}}\left(c(x,y,t)\nabla I\right)=\nabla c\cdot \nabla I+c(x,y,t)\Delta I\f]
Suggested functions for c(x,y,t) are:
\f[c\left(\|\nabla I\|\right)=e^{{-\left(\|\nabla I\|/K\right)^{2}}}\f]
or
\f[ c\left(\|\nabla I\|\right)={\frac {1}{1+\left({\frac {\|\nabla I\|}{K}}\right)^{2}}} \f]
@param src Grayscale Source image.
@param dst Destination image of the same size and the same number of channels as src .
@param alpha The amount of time to step forward by on each iteration (normally, it's between 0 and 1).
@param K sensitivity to the edges
@param niters The number of iterations
*/
CV_EXPORTS_W void anisotropicDiffusion(InputArray src, OutputArray dst, float alpha, float K, int niters );
//! @}
......
/*M///////////////////////////////////////////////////////////////////////////////////////
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#include "opencv2/core/utility.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/imgcodecs.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/ximgproc.hpp"
#include <stdio.h>
using namespace cv;
using namespace std;
int main( int argc, const char** argv)
{
float alpha = 1.0f;
float sigma = 0.02f;
int rows0 = 480;
int niters = 10;
Mat frame, src, dst;
const char* window_name = "Anisodiff : Exponential Flux";
VideoCapture cap;
if( argc > 1 )
cap.open(argv[1]);
else
cap.open(0);
if (!cap.isOpened())
{
printf("Cannot initialize video capturing\n");
return 0;
}
// Create a window
namedWindow(window_name, 1);
// create a toolbar
createTrackbar("No. of time steps", window_name, &niters, 30, 0);
for(;;)
{
cap >> frame;
if( frame.empty() )
break;
if( frame.rows <= rows0 )
src = frame;
else
resize(frame, src, Size(cvRound(480.*frame.cols/frame.rows), 480));
float t = (float)getTickCount();
ximgproc::anisotropicDiffusion(src, dst, alpha, sigma, niters);
t = (float)getTickCount() - t;
printf("time: %.1fms\n", t*1000./getTickFrequency());
imshow(window_name, dst);
// Wait for a key stroke; the same function arranges events processing
char c = (char)waitKey(30);
if(c >= 0)
break;
}
return 0;
}
This diff is collapsed.
__kernel void anisodiff(__global const uchar * srcptr, int srcstep, int srcoffset,
__global uchar * dstptr, int dststep, int dstoffset,
int rows, int cols, __constant float* exptab, float alpha)
{
int x = get_global_id(0);
int y = get_global_id(1);
if( x < cols && y < rows )
{
int yofs = y*dststep + x*3;
int xofs = y*srcstep + x*3;
float4 s = 0.f;
float4 c = (float4)(srcptr[xofs], srcptr[xofs+1], srcptr[xofs+2], 0.f);
float4 delta, adelta;
float w;
#define UPDATE_SUM(xofs1) \
delta = (float4)(srcptr[xofs + xofs1], srcptr[xofs + xofs1 + 1], srcptr[xofs + xofs1 + 2], 0.f) - c; \
adelta = fabs(delta); \
w = exptab[convert_int(adelta.x + adelta.y + adelta.z)]; \
s += delta*w
UPDATE_SUM(3);
UPDATE_SUM(-3);
UPDATE_SUM(-srcstep-3);
UPDATE_SUM(-srcstep);
UPDATE_SUM(-srcstep+3);
UPDATE_SUM(srcstep-3);
UPDATE_SUM(srcstep);
UPDATE_SUM(srcstep+3);
s = s*alpha + c;
uchar4 d = convert_uchar4_sat(convert_int4_rte(s));
dstptr[yofs] = d.x;
dstptr[yofs+1] = d.y;
dstptr[yofs+2] = d.z;
}
}
#include "test_precomp.hpp"
using namespace cv;
using namespace std;
TEST(ximgproc_AnisotropicDiffusion, regression)
{
string folder = string(cvtest::TS::ptr()->get_data_path()) + "shared/";
string original_path = folder + "fruits.png";
Mat original = imread(original_path, IMREAD_COLOR);
ASSERT_FALSE(original.empty()) << "Could not load input image " << original_path;
ASSERT_EQ(3, original.channels()) << "Load color input image " << original_path;
Mat result;
float alpha = 1.0f;
float K = 0.02f;
int niters = 10;
ximgproc::anisotropicDiffusion(original, result, alpha, K, niters);
double adiff_psnr = cvtest::PSNR(original, result);
//printf("psnr=%.2f\n", adiff_psnr);
ASSERT_GT(adiff_psnr, 25.0);
}
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