OpenCV笔记：滤波器

void boxFilter( InputArray src, OutputArray dst, int ddepth,                 Size ksize, Point anchor=Point(-1,-1),                 bool normalize=true,                 int borderType=BORDER_DEFAULT ); 

static void on_box_filter(int, void *) {     if (box_filter_size < 3)         box_filter_size = 3;     boxFilter(lena_bmp, box_filter_bmp, -1, Size(box_filter_size, box_filter_size));     imshow("Box Filter", box_filter_bmp); }  int main() {         lena_bmp = imread("../lena.bmp");      namedWindow("Box Filter", 1);     createTrackbar("Size", "Box Filter", &box_filter_size, 40, on_box_filter);     imshow("Box Filter", lena_bmp);     waitKey(0); }

void blur( InputArray src, OutputArray dst,            Size ksize, Point anchor=Point(-1,-1),            int borderType=BORDER_DEFAULT );

static void on_blur_filter(int, void *) {        blur(lena+bmp, blur_test_bmp, Size(blur_size, blur_size));     imshow("Blur Filter", blur_test_bmp); }  int main() {     lena_bmp = imread("../lena.bmp");     namedWindow("Blur Filter", 1);     createTrackbar("Size", "Blur Filter", &blur_size, on_blur_filter);     imshow("Blur Filter", lena_bmp);     waitKey(0); }

void GaussianBlur( InputArray src,                    OutputArray dst, Size ksize,                    double sigmaX, double sigmaY=0,                    int borderType=BORDER_DEFAULT );

static void on_gaussian_blur(int, void *) {     if (gaussian_blur_size < 1)          gaussian_blur_size = 1;     GaussianBlur(lena_bmp, gaussian_blur_bmp, Size(gaussian_blur_size * 2 + 1,          gaussian_blur_size * 2 + 1), gaussian_sigma_x / 10.0, gaussian_sigma_y / 10.0);     imshow("Gaussian Blur", gaussian_blur_bmp); }  int main() {     lena_bmp = imread("../lena.bmp");     namedWindow("Gaussian Blur", 1);     createTrackbar("Size", "Gaussian Blur", &gaussian_blur_size, 40, on_gaussian_blur);     createTrackbar("SigmaX", "Gaussian Blur", &gaussian_sigma_x, 100, on_gaussian_blur);     createTrackbar("SigmaY", "Gaussian Blur", &gaussian_sigma_y, 100, on_gaussian_blur);     imshow("Gaussian Blur", lena_bmp);     waitKey(0); }

void medianBlur( InputArray src, OutputArray dst, int ksize );

static void on_median_blur(int, void *) {     if (median_size < 3)          median_size = 3;     medianBlur(lena_bmp, median_blur_bmp, median_size * 2 + 1);     imshow("Median Blur", median_blur_bmp); }  int main() {     lena_bmp = imread("../lena.bmp");     namedWindow("Median Blur", 1);     createTrackbar("Median Size:", "Median Blur", &median_size, 40, on_median_blur);     imshow("Median Blur", lena_bmp);     waitKey(0); }

void sepFilter2D( InputArray src, OutputArray dst, int ddepth,                   InputArray kernelX, InputArray kernelY,                   Point anchor=Point(-1,-1),                   double delta=0, int borderType=BORDER_DEFAULT );

void test_filter2d() {     /* 注意类型 */     Mat kernel3 = (Mat_<char>(3, 3) << 1, 2, 1,                                     0, 0, 0,                                      -1, -2, -1);     Mat filter2d_bmp;     filter2D(lena_bmp, filter2d_bmp, lena_bmp.depth(), kernel3);     namedWindow("Filter2D", 1);     imshow("Filter2D", filter2d_bmp); }  int main() {     lena_bmp = imread("../lena.bmp");     test_filter2d();     waitKey(0); }

void bilateralFilter( InputArray src, OutputArray dst, int d,                       double sigmaColor, double sigmaSpace,                       int borderType=BORDER_DEFAULT );

double generate_gaussian_noise(double mu, double sigma) {     const double epsilon = std::numeric_limits<double>::min();     static double z0, z1;     static bool flag = false;     flag = !flag;     if (!flag)         return z1*sigma + mu;     double u1, u2;     do {         u1 = rand()*(1.0 / RAND_MAX);         u2 = rand()*(1.0 / RAND_MAX);     } while (u1 <= epsilon);     z0 = sqrt(-2.0*log(u1))*cos(2.0*CV_PI*u2);     z1 = sqrt(-2.0*log(u1))*sin(2.0*CV_PI*u2);     return z0*sigma + mu; }  void add_gaussian_noise(const Mat& src, Mat& dst, double mu, double sigma) {     dst = src.clone();     int channels = dst.channels();     int nrows = dst.rows;     int ncols = dst.cols*channels;     if (dst.isContinuous()) {         ncols *= nrows;         nrows = 1;     }     for (int i = 0; i < nrows; i++)         for (int j = 0; j < ncols; j++) {             dst.ptr<uchar>(i)[j] = saturate_cast<uchar>(dst.ptr<uchar>(i)[j] +                  generate_gaussian_noise(mu, sigma) * 32);         } }  static void on_bilateral_filter(int, void *) {     bilateralFilter(gaussian_noise_bmp, bilateral_bmp, d - 5, sigma_color*1.0, sigma_space*1.0);     imshow("Bilateral Filter", bilateral_bmp); }  int main() {     namedWindow("Bilateral Filter", 1);     add_gaussian_noise(lena_bmp, gaussian_noise_bmp, -2, 4.5);     createTrackbar("d", "Bilateral Filter", &d, 20, on_bilateral_filter);     createTrackbar("Color", "Bilateral Filter", &sigma_color, 500, on_bilateral_filter);     createTrackbar("Space", "Bilateral Filter", &sigma_space, 500, on_bilateral_filter);     waitKey(0); }

文章来源: OpenCV笔记：滤波器