图像各向异性滤波

#include <opencv2/opencv.hpp>

#include <iostream>


using namespace cv;

using namespace std;

float k = 15;

float lambda = 0.25;

int N = 20;


void anisotropy_demo(Mat &image, Mat &result);

int main(int argc, char** argv) {

    Mat src = imread("D:/vcprojects/images/example.png");

    if (src.empty()) {

        printf("could not load image...\n");

        return -1;

    }

    namedWindow("input image", CV_WINDOW_AUTOSIZE);

    imshow("input image", src);

    vector<Mat> mv;

    vector<Mat> results;

    split(src, mv);

    for (int n = 0; n < mv.size(); n++) {

        Mat m = Mat::zeros(src.size(), CV_32FC1);

        mv[n].convertTo(m, CV_32FC1);

        results.push_back(m);

    }


    int w = src.cols;

    int h = src.rows;

    Mat copy = Mat::zeros(src.size(), CV_32FC1);

    for (int i = 0; i < N; i++) {

        anisotropy_demo(results[0], copy);

        copy.copyTo(results[0]);


        anisotropy_demo(results[1], copy);

        copy.copyTo(results[1]);


        anisotropy_demo(results[2], copy);

        copy.copyTo(results[2]);


    }

    Mat output;

    normalize(results[0], results[0], 0, 255, NORM_MINMAX);

    normalize(results[1], results[1], 0, 255, NORM_MINMAX);

    normalize(results[2], results[2], 0, 255, NORM_MINMAX);


    results[0].convertTo(mv[0], CV_8UC1);

    results[1].convertTo(mv[1], CV_8UC1);

    results[2].convertTo(mv[2], CV_8UC1);


    Mat dst;

    merge(mv, dst);


    imshow("result", dst);

    imwrite("D:/result.png", dst);

    waitKey(0);

    return 0;

}


void anisotropy_demo(Mat &image, Mat &result) {

    int width = image.cols;

    int height = image.rows;


    // 四邻域梯度

    float n = 0, s = 0, e = 0, w = 0; 

    // 四邻域系数

    float nc = 0, sc = 0, ec = 0, wc = 0; 

    float k2 = k*k;

    for (int row = 1; row < height -1; row++) {

        for (int col = 1; col < width -1; col++) {

            // gradient

            n = image.at<float>(row - 1, col) - image.at<float>(row, col);

            s = image.at<float>(row + 1, col) - image.at<float>(row, col);

            e = image.at<float>(row, col - 1) - image.at<float>(row, col);

            w = image.at<float>(row, col + 1) - image.at<float>(row, col);

            nc = exp(-n*n / k2);

            sc = exp(-s*s / k2);

            ec = exp(-e*e / k2);

            wc = exp(-w*w / k2);

            result.at<float>(row, col) = image.at<float>(row, col) + lambda*(n*nc + s*sc + e*ec + w*wc);

        }

    }

}