在家做网站设计挣钱吗,行业网站导航,wordpress访问量,哪家企业网站做的好目录源码滤波器主函数效果完整源码平台#xff1a;Windows 10 20H2 Visual Studio 2015 OpenCV 4.5.3 本文所用源码修改自双边滤波(bilateral filter)以及联合双边滤波#xff08;joint bilateral filter#xff09;—— flow_specter
源码
滤波器
// 双边滤波
// src…
目录源码滤波器主函数效果完整源码平台Windows 10 20H2 Visual Studio 2015 OpenCV 4.5.3 本文所用源码修改自双边滤波(bilateral filter)以及联合双边滤波joint bilateral filter—— flow_specter
源码
滤波器
// 双边滤波
// src 待滤波的影像
// dst 输出的影像
void BilateralFilter(Mat src, Mat dst, int d, double sigmaColor, double sigmaSpace)
{dst src.clone();int n_rows dst.rows;int n_cols dst.cols;int n_channels dst.channels();int n_cols_with_channels n_cols * n_channels;int half_kernel_size d / 2;int index;double pixel_sum;double weight_sum 0;double temp_bilateral_weight 0;double color_kernel[256];// 颜色域权重确定// color_kernel 颜色域核1D长度为256for (int i 0; i 256; i){color_kernel[i] exp(-1.0 * (i * i) / (2 * sigmaColor * sigmaColor));}// 空间域权重确定// distance_kernel 空间域核,1D// **************************************************************************************************************double *distance_kernel;distance_kernel new double[d * d];int k d / 2;//二维动态数组申请空间double **distance_kernel_2D new double*[d];for (int i 0; i d; i)distance_kernel_2D[i] new double[d];double delta_square 2 * sigmaSpace * sigmaSpace; //分母for (int i -k; i k; i){for (int j -k; j k; j){double distance_numerator i * i j * j;distance_kernel_2D[i k][j k] exp(-1.0 * distance_numerator / delta_square);}}// 将2D kernel 转换为 1D kernelfor (int i 0; i d; i){for (int j 0; j d; j){distance_kernel[d * i j] distance_kernel_2D[i][j];}}//释放二维动态数组空间for (int i 0; i d; i)delete[] distance_kernel_2D[i];delete[] distance_kernel_2D;// **************************************************************************************************************// 边界不做处理for (int i half_kernel_size; i (n_rows - half_kernel_size); i) {uchar* pt_dst dst.ptruchar(i);uchar* pt_src src.ptruchar(i);for (int j n_channels * half_kernel_size; j (n_cols_with_channels - n_channels * half_kernel_size); j) {index 0;pixel_sum weight_sum 0;// 内层kx,ky循环,空间域内滤波for (int kx i - half_kernel_size; kx i half_kernel_size; kx) {uchar* pt_k_src src.ptruchar(kx);for (int ky j - n_channels * half_kernel_size; ky (j n_channels * half_kernel_size); ky n_channels) {temp_bilateral_weight distance_kernel[index] * color_kernel[(int)abs(pt_src[j] - pt_k_src[ky])];weight_sum temp_bilateral_weight;pixel_sum (pt_k_src[ky] * temp_bilateral_weight); // 邻域某像素与中心点的双边权重乘积}}pixel_sum / weight_sum; // 归一化pt_dst[j] saturate_castuchar(pixel_sum); //加权赋值}}delete[]distance_kernel;
}
//————————————————
//版权声明本文为CSDN博主「flow_specter」的原创文章遵循CC 4.0 BY - SA版权协议转载请附上原文出处链接及本声明。
//原文链接https ://blog.csdn.net/flow_specter/article/details/107557303主函数
图片路径根据实际情况调整注意反斜杠是转义字符的开头故“\”应替换为“\”
int main(int argc, char * argv[])
{Mat src imread(D:\\Work\\OpenCV\\Workplace\\Test_1\\face.jpg);Mat dst;BilateralFilter(src, dst, 23, 35, 10);imshow(原图, src);imshow(输出, dst);waitKey(0);return 0;
}效果 完整源码
#include opencv2\opencv.hpp
#include iostreamusing namespace cv;
using namespace std;// 双边滤波
// src 待滤波的影像
// dst 输出的影像
void BilateralFilter(Mat src, Mat dst, int d, double sigmaColor, double sigmaSpace)
{dst src.clone();int n_rows dst.rows;int n_cols dst.cols;int n_channels dst.channels();int n_cols_with_channels n_cols * n_channels;int half_kernel_size d / 2;int index;double pixel_sum;double weight_sum 0;double temp_bilateral_weight 0;double color_kernel[256];// 颜色域权重确定// color_kernel 颜色域核1D长度为256for (int i 0; i 256; i){color_kernel[i] exp(-1.0 * (i * i) / (2 * sigmaColor * sigmaColor));}// 空间域权重确定// distance_kernel 空间域核,1D// **************************************************************************************************************double *distance_kernel;distance_kernel new double[d * d];int k d / 2;//二维动态数组申请空间double **distance_kernel_2D new double*[d];for (int i 0; i d; i)distance_kernel_2D[i] new double[d];double delta_square 2 * sigmaSpace * sigmaSpace; //分母for (int i -k; i k; i){for (int j -k; j k; j){double distance_numerator i * i j * j;distance_kernel_2D[i k][j k] exp(-1.0 * distance_numerator / delta_square);}}// 将2D kernel 转换为 1D kernelfor (int i 0; i d; i){for (int j 0; j d; j){distance_kernel[d * i j] distance_kernel_2D[i][j];}}//释放二维动态数组空间for (int i 0; i d; i)delete[] distance_kernel_2D[i];delete[] distance_kernel_2D;// **************************************************************************************************************// 边界不做处理for (int i half_kernel_size; i (n_rows - half_kernel_size); i) {uchar* pt_dst dst.ptruchar(i);uchar* pt_src src.ptruchar(i);for (int j n_channels * half_kernel_size; j (n_cols_with_channels - n_channels * half_kernel_size); j) {index 0;pixel_sum weight_sum 0;// 内层kx,ky循环,空间域内滤波for (int kx i - half_kernel_size; kx i half_kernel_size; kx) {uchar* pt_k_src src.ptruchar(kx);for (int ky j - n_channels * half_kernel_size; ky (j n_channels * half_kernel_size); ky n_channels) {temp_bilateral_weight distance_kernel[index] * color_kernel[(int)abs(pt_src[j] - pt_k_src[ky])];weight_sum temp_bilateral_weight;pixel_sum (pt_k_src[ky] * temp_bilateral_weight); // 邻域某像素与中心点的双边权重乘积}}pixel_sum / weight_sum; // 归一化pt_dst[j] saturate_castuchar(pixel_sum); //加权赋值}}delete[]distance_kernel;
}
//————————————————
//版权声明本文为CSDN博主「flow_specter」的原创文章遵循CC 4.0 BY - SA版权协议转载请附上原文出处链接及本声明。
//原文链接https ://blog.csdn.net/flow_specter/article/details/107557303int main(int argc, char * argv[])
{Mat src imread(D:\\Work\\OpenCV\\Workplace\\Test_1\\face.jpg);Mat dst;BilateralFilter(src, dst, 23, 35, 10);imshow(原图, src);imshow(输出, dst);waitKey(0);return 0;
}
