b站：https://www.bilibili.com/video/BV1uW411d7Wf?p=5
下面是我在b站上看視頻學習的筆記和操作的示例代碼

實例代碼

#include<opencv2/opencv.hpp> #include<iostream> #include<math.h>using namespace cv;int main(int argc, char** argv) {Mat src, dst;src = imread("E:/picture/pic_cv/pic.jpg");if (!src.data) {printf("Could not load image...\n");return -1;}namedWindow("input image", WINDOW_AUTOSIZE);imshow("input image", src);//-------------------------------------------------------------------------//----------------------【自定義掩膜操作過程】-----------------------------//------------------------------------------------------------------------int cols = src.cols * src.channels();//RGB圖像是三通道圖像int offsetx = src.channels();//左右漂移多少是通道數(shù)決定的int rows = src.rows;dst = Mat::zeros(src.size(), src.type());//對dst圖像矩陣初始化為src的大小和類型 //一定要注意初始化！！for (int row = 1; row < (rows - 1); row++) {const uchar* previous = src.ptr<uchar>(row - 1);uchar* current = src.ptr<uchar>(row);const uchar* next = src.ptr<uchar>(row + 1);uchar* output = dst.ptr<uchar>(row);//創(chuàng)建指針指向dst的row行for (int col = offsetx; col < cols - offsetx; col++){//方法一：這樣出來的圖像跟麻臉一樣，因為有的數(shù)據(jù)超過了255，或小于0，造成溢出//output[col] = 5 * current[col] - (current[col - offsetx] + current[col + offsetx] + previous[col] + next[col]);//方法二：用saturate_cast（飽和函數(shù)）函數(shù) 處理溢出數(shù)據(jù)output[col] = saturate_cast<uchar>(5 * current[col] - (current[col - offsetx] + current[col + offsetx] + previous[col] + next[col]));}}//-------------------------------------------------------------------------//----------------------【end1】-----------------------------//------------------------------------------------------------------------namedWindow("contrast image demo 1", WINDOW_AUTOSIZE);imshow("contrast image demo 1", dst);//-------------------------------------------------------------------------//----------------------【調用filter2D函數(shù)操作】-----------------------------//------------------------------------------------------------------------double t = getTickCount();Mat kernel = (Mat_<char>(3, 3) << 0, -1, 0,-1, 5, -1,0, -1, 0);filter2D(src, dst, src.depth(), kernel);double timeconsume = (getTickCount() - t) / getTickFrequency();printf("time consume :%.2lf", timeconsume);//-------------------------------------------------------------------------//----------------------【end2】-----------------------------//------------------------------------------------------------------------namedWindow("contrast image demo 2", WINDOW_AUTOSIZE);imshow("contrast image demo 2", dst);waitKey(0);return 0; }

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