C++双边滤波 C++图像处理之双边滤波
Asimov_Liu 人气:0想了解C++图像处理之双边滤波的相关内容吗,Asimov_Liu在本文为您仔细讲解C++双边滤波的相关知识和一些Code实例,欢迎阅读和指正,我们先划重点:C++,双边滤波,下面大家一起来学习吧。
1、 近期在学习双边滤波相关知识,其原理如下(以后补上):
2 、灰度图双边滤波实现C++代码如下,网上大多数是基于8位灰度图和彩色图像的。(此次代码未经优化,可去除opencv依赖):
//灰度图双边滤波 void m_bilateralFilter(cv::Mat src,cv::Mat& dst,int radius,float sigma_r,float sigma_d) { if (src.empty()) return; if (dst.empty()) { dst = src.clone(); } if (src.depth() == CV_16U){ for (int i = radius; i < src.rows - radius; i++) for (int j = radius; j < src.cols - radius; j++) { float sum_1 = .0f, sum_2 = .0f; for (int k = 0; k < 2 * radius - 1; k++) for (int l = 0; l < 2 * radius - 1; l++) { int dis_x = radius - k; int dis_y = radius - l; int coord_x_image = i - radius + k; int coord_y_image = j - radius + l; float dis_spatial = dis_x*dis_x + dis_y*dis_y; float dis_range = (src.at<unsigned short>(i, j) - src.at<unsigned short>(coord_x_image, coord_y_image))*(src.at<unsigned short>(i, j) - src.at<unsigned short>(coord_x_image, coord_y_image)); float c_tmp = exp(-dis_spatial / (2 * sigma_d * sigma_d)); float s_tmp = exp(-dis_range / (2 * sigma_r * sigma_r)); sum_1 += c_tmp*s_tmp*src.at<unsigned short>(coord_x_image, coord_y_image); sum_2 += c_tmp*s_tmp; } dst.at<unsigned short>(i, j) = sum_1 / sum_2; } } else if (src.depth() == CV_8U) { for (int i = radius; i < src.rows - radius; i++) for (int j = radius; j < src.cols - radius; j++) { float sum_1 = .0f, sum_2 = .0f; for (int k = 0; k < 2 * radius - 1; k++) for (int l = 0; l < 2 * radius - 1; l++) { int dis_x = radius - k; int dis_y = radius - l; int coord_x_image = i - radius + k; int coord_y_image = j - radius + l; float dis_spatial = dis_x*dis_x + dis_y*dis_y; float dis_range = (src.at<unsigned char>(i, j) - src.at<unsigned char>(coord_x_image, coord_y_image))*(src.at<unsigned char>(i, j) - src.at<unsigned char>(coord_x_image, coord_y_image)); float c_tmp = exp(-dis_spatial / (2 * sigma_d * sigma_d)); float s_tmp = exp(-dis_range / (2 * sigma_r * sigma_r)); sum_1 += c_tmp*s_tmp*src.at<unsigned char>(coord_x_image, coord_y_image); sum_2 += c_tmp*s_tmp; } dst.at<unsigned char>(i, j) = sum_1 / sum_2; } } }
3、目前是基于单通道图像,效果如下:
原图:
opencv 库的效果(cv::bilateralFilter(img_src, img_dst, 10,10 * 2, 10 / 2))
该程序的效果(m_bilateralFilter(img_src, img_dst, 5, 10 * 2, 10 / 2))
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