OpenCv 027---均值迁移滤波

/** @brief Performs initial step of meanshift segmentation of an image.
The function implements the filtering stage of meanshift segmentation, that is, the output of the
function is the filtered "posterized" image with color gradients and fine-grain texture flattened.
At every pixel (X,Y) of the input image (or down-sized input image, see below) the function executes
meanshift iterations, that is, the pixel (X,Y) neighborhood in the joint space-color hyperspace is
considered:
\f[(x,y): X- \texttt{sp} \le x  \le X+ \texttt{sp} , Y- \texttt{sp} \le y  \le Y+ \texttt{sp} , ||(R,G,B)-(r,g,b)||   \le \texttt{sr}\f]
where (R,G,B) and (r,g,b) are the vectors of color components at (X,Y) and (x,y), respectively
(though, the algorithm does not depend on the color space used, so any 3-component color space can
be used instead). Over the neighborhood the average spatial value (X',Y') and average color vector
(R',G',B') are found and they act as the neighborhood center on the next iteration:
\f[(X,Y)~(X',Y'), (R,G,B)~(R',G',B').\f]
After the iterations over, the color components of the initial pixel (that is, the pixel from where
the iterations started) are set to the final value (average color at the last iteration):
\f[I(X,Y) <- (R*,G*,B*)\f]
When maxLevel \> 0, the gaussian pyramid of maxLevel+1 levels is built, and the above procedure is
run on the smallest layer first. After that, the results are propagated to the larger layer and the
iterations are run again only on those pixels where the layer colors differ by more than sr from the
lower-resolution layer of the pyramid. That makes boundaries of color regions sharper. Note that the
results will be actually different from the ones obtained by running the meanshift procedure on the
whole original image (i.e. when maxLevel==0).
@param src The source 8-bit, 3-channel image.
@param dst The destination image of the same format and the same size as the source.
@param sp The spatial window radius.
@param sr The color window radius.
@param maxLevel Maximum level of the pyramid for the segmentation.
@param termcrit Termination criteria: when to stop meanshift iterations.
 */
CV_EXPORTS_W void pyrMeanShiftFiltering( InputArray src, OutputArray dst,
                                         double sp, double sr, int maxLevel = 1,
                                         TermCriteria termcrit=TermCriteria(TermCriteria::MAX_ITER+TermCriteria::EPS,5,1) );

#include <opencv2/opencv.hpp>
#include <iostream>

using namespace cv;
using namespace std;

int main(int artc, char** argv) {
    Mat src = imread("images/Demo.jpg");
    if (src.empty()) {
        printf("could not load image...\n");
        return -1;
    }
    namedWindow("input", CV_WINDOW_AUTOSIZE);
    imshow("input", src);

    Mat dst;
    pyrMeanShiftFiltering(src, dst, 15, 50, 1, TermCriteria(TermCriteria::COUNT + TermCriteria::EPS, 5, 1));
    imshow("result", dst);

    waitKey(0);
    return 0;
}