图像滤波在opencv中可以有多种实现形式
自定义滤波
如使用3×3的掩模:
对图像进行处理.
使用函数filter2D()实现
- #include<opencv2/opencv.hpp>
- using namespace cv;
- int main()
- {
- //函数调用filter2D功能
- Mat src,dst;
- src = imread("E:/image/image/daibola.jpg");
- if(!src.data)
- {
- printf("can not load image \n");
- return -1;
- }
- namedWindow("input", CV_WINDOW_AUTOSIZE);
- imshow("input", src);
- src.copyTo(dst);
- Mat kernel = (Mat_<int>(3,3)<<1,1,1,1,1,-1,-1,-1,-1);
- double t = (double)getTickCount();
- filter2D(src, dst, src.depth(), kernel);
- std::cout<<((double)getTickCount()-t)/getTickFrequency()<<std::endl;
- namedWindow("output", CV_WINDOW_AUTOSIZE);
- imshow("output", dst);
- printf("%d",src.channels());
- waitKey();
- return 0;
- }
通过像素点操作实现
- #include<opencv2/opencv.hpp>
- using namespace cv;
- int main()
- {
- Mat src, dst;
- src = imread("E:/image/image/daibola.jpg");
- CV_Assert(src.depth() == CV_8U);
- if(!src.data)
- {
- printf("can not load image \n");
- return -1;
- }
- namedWindow("input", CV_WINDOW_AUTOSIZE);
- imshow("input",src);
- src.copyTo(dst);
- for(int row = 1; row<(src.rows - 1); row++)
- {
- const uchar* previous = src.ptr<uchar>(row - 1);
- const uchar* current = src.ptr<uchar>(row);
- const uchar* next = src.ptr<uchar>(row + 1);
- uchar* output = dst.ptr<uchar>(row);
- for(int col = src.channels(); col < (src.cols - 1)*src.channels(); col++)
- {
- *output = saturate_cast<uchar>(1 * current[col] + previous[col] - next[col] + current[col - src.channels()] - current[col + src.channels()]);
- output++;
- }
- }
- namedWindow("output", CV_WINDOW_AUTOSIZE);
- imshow("output",dst);
- waitKey();
- return 0;
- }
特定形式滤波
常用的有:
blur(src,dst,Size(5,5));均值滤波
GaussianBlur(src,dst,Size(5,5),11,11);高斯滤波
medianBlur(src,dst,5);中值滤波(应对椒盐噪声)
bilateralFilter(src,dst,2,0.5,2,4);双边滤波(保留边缘)
- #include<opencv2/opencv.hpp>
- using namespace cv;
- int main()
- {
- Mat src, dst;
- src = imread("E:/image/image/daibola.jpg");
- CV_Assert(src.depth() == CV_8U);
- if(!src.data)
- {
- printf("can not load image \n");
- return -1;
- }
- namedWindow("input", CV_WINDOW_AUTOSIZE);
- imshow("input",src);
- src.copyTo(dst);
- //均值滤波
- blur(src,dst,Size(5,5));
- //中值滤波
- //medianBlur(src,dst,5);
- namedWindow("output", CV_WINDOW_AUTOSIZE);
- imshow("output",dst);
- waitKey();
- return 0;
- }
以上这篇opencv3/C++图像滤波实现方式就是小编分享给大家的全部内容了,希望能给大家一个参考,也希望大家多多支持我们。
原文链接:https://blog.csdn.net/akadiao/article/details/78836879