矩阵的掩膜操作 用于图片增强对比度。
可通过构造掩膜 使用filter2D()
#include <iostream> #include <opencv2/core/core.hpp> #include <opencv2/highgui/highgui.hpp> #include <opencv2/opencv.hpp> using namespace std; using namespace cv; int main() { Mat src = imread("/Users/apple/Desktop/test3.png", IMREAD_COLOR); if (src.empty()) { // if (!src.data()) cout << "could not load image..." << endl; return -1; } namedWindow("test opencv setup", CV_WINDOW_AUTOSIZE); imshow("test opencv setup", src); // int cols = src.cols * src.channels(); // int rows = src.rows; // int offsetx = src.channels(); // // // for (int row = 1; row < rows - 1; row++) { // const uchar* current = src.ptr<uchar>(row); // const uchar* next = src.ptr<uchar>(row + 1); // const uchar* previous = src.ptr<uchar>(row - 1); // uchar* output = dst.ptr(row); // for (int col = offsetx; col < cols; col++) { // output[col] = saturate_cast<uchar>(5 * current[col] - (current[col - offsetx] + current[col + offsetx] + previous[col] + next[col])); // } // } // 注意 saturate_cast<>() 的用法: 控制值在0~255之前 Mat dst; 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 timeconsum = (getTickCount() - t) / getTickFrequency(); cout << "spent: " << timeconsum << endl; namedWindow("contrast image demo", CV_WINDOW_AUTOSIZE); imshow("contrast image demo", dst); waitKey(0); return 0; }
注意saturate_cast<>()的使用,控制值在0~255之间。
还有一个知识点:
通过调用getTickCount() 和 getTickFrequency()来计算所用时间。