目錄

• 源碼
• • 濾波器
  • 主函數(shù)
• 效果
• 完整源碼

平臺(tái)：Windows 10 20H2
Visual Studio 2015
OpenCV 4.5.3

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本文所用源碼修改自雙邊濾波(bilateral filter)以及聯(lián)合雙邊濾波（joint bilateral filter）—— flow_specter

源碼

濾波器

// 雙邊濾波 // @ src 待濾波的影像 // @ dst 輸出的影像 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];// 顏色域權(quán)重確定// @ color_kernel 顏色域核，1D，長度為256for (int i = 0; i < 256; i++){color_kernel[i] = exp(-1.0 * (i * i) / (2 * sigmaColor * sigmaColor));}// 空間域權(quán)重確定// @ distance_kernel 空間域核,1D// **************************************************************************************************************double *distance_kernel;distance_kernel = new double[d * d];int k = d / 2;//二維動(dòng)態(tài)數(shù)組申請空間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);}}// 將2D kernel 轉(zhuǎn)換為 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];}}//釋放二維動(dòng)態(tài)數(shù)組空間for (int i = 0; i < d; i++)delete[] distance_kernel_2D[i];delete[] distance_kernel_2D;// **************************************************************************************************************// 邊界不做處理for (int i = half_kernel_size; i < (n_rows - half_kernel_size); i++) {uchar* pt_dst = dst.ptr<uchar>(i);uchar* pt_src = src.ptr<uchar>(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;// 內(nèi)層kx,ky循環(huán),空間域內(nèi)濾波for (int kx = i - half_kernel_size; kx <= i + half_kernel_size; kx++) {uchar* pt_k_src = src.ptr<uchar>(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); // 鄰域某像素與中心點(diǎn)的雙邊權(quán)重乘積}}pixel_sum /= weight_sum; // 歸一化pt_dst[j] = saturate_cast<uchar>(pixel_sum); //加權(quán)賦值}}delete[]distance_kernel; } //———————————————— //版權(quán)聲明：本文為CSDN博主「flow_specter」的原創(chuàng)文章，遵循CC 4.0 BY - SA版權(quán)協(xié)議，轉(zhuǎn)載請附上原文出處鏈接及本聲明。 //原文鏈接：https ://blog.csdn.net/flow_specter/article/details/107557303

主函數(shù)

圖片路徑根據(jù)實(shí)際情況調(diào)整，注意反斜杠是轉(zhuǎn)義字符的開頭，故“\”應(yīng)替換為“\”

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("原圖", src);imshow("輸出", dst);waitKey(0);return 0; }

效果

完整源碼

#include <opencv2\opencv.hpp> #include <iostream>using namespace cv; using namespace std;// 雙邊濾波 // @ src 待濾波的影像 // @ dst 輸出的影像 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];// 顏色域權(quán)重確定// @ color_kernel 顏色域核，1D，長度為256for (int i = 0; i < 256; i++){color_kernel[i] = exp(-1.0 * (i * i) / (2 * sigmaColor * sigmaColor));}// 空間域權(quán)重確定// @ distance_kernel 空間域核,1D// **************************************************************************************************************double *distance_kernel;distance_kernel = new double[d * d];int k = d / 2;//二維動(dòng)態(tài)數(shù)組申請空間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);}}// 將2D kernel 轉(zhuǎn)換為 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];}}//釋放二維動(dòng)態(tài)數(shù)組空間for (int i = 0; i < d; i++)delete[] distance_kernel_2D[i];delete[] distance_kernel_2D;// **************************************************************************************************************// 邊界不做處理for (int i = half_kernel_size; i < (n_rows - half_kernel_size); i++) {uchar* pt_dst = dst.ptr<uchar>(i);uchar* pt_src = src.ptr<uchar>(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;// 內(nèi)層kx,ky循環(huán),空間域內(nèi)濾波for (int kx = i - half_kernel_size; kx <= i + half_kernel_size; kx++) {uchar* pt_k_src = src.ptr<uchar>(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); // 鄰域某像素與中心點(diǎn)的雙邊權(quán)重乘積}}pixel_sum /= weight_sum; // 歸一化pt_dst[j] = saturate_cast<uchar>(pixel_sum); //加權(quán)賦值}}delete[]distance_kernel; } //———————————————— //版權(quán)聲明：本文為CSDN博主「flow_specter」的原創(chuàng)文章，遵循CC 4.0 BY - SA版權(quán)協(xié)議，轉(zhuǎn)載請附上原文出處鏈接及本聲明。 //原文鏈接：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("原圖", src);imshow("輸出", dst);waitKey(0);return 0; } 創(chuàng)作挑戰(zhàn)賽新人創(chuàng)作獎(jiǎng)勵(lì)來咯，堅(jiān)持創(chuàng)作打卡瓜分現(xiàn)金大獎(jiǎng)

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