理论
像素变换可看成点操作;
邻域操作可看成区域;
调整图像亮度和对比度属于像素变换--点操作
示例:
#include <opencv2\opencv.hpp>
#include <iostream>
using namespace std;
using namespace cv;
int main(void)
{
Mat src, dst;
src = imread("F:/test.png");
if (!src.data) {
cout << "open picture erro!!" << endl;
return -1;
}
//cvtColor(src, src, CV_BGR2GRAY); /*测试单通道的灰度图像*/
int height = src.rows;
int width = src.cols;
dst = Mat::zeros(src.size(), src.type()); /*创建一张与原图像大小和类型一致的空白图像,像素值初始化为0*/
float alpha = 1.4;
float beta = 20;
for (int row = 0; row < height; row++) {
for (int col = 0; col < width; col++) {
if (src.channels() == 1) { /*单通道*/
float v = src.at<uchar>(row, col);
dst.at<uchar>(row, col) = saturate_cast<uchar>(v * alpha + beta);/*确保值大小在0-255之间*/
}
else if (src.channels() == 3) { /*多通道*/
float b = src.at<Vec3b>(row, col)[0];
float g = src.at<Vec3b>(row, col)[1];
float r = src.at<Vec3b>(row, col)[2];
/*给每个像素点每个通道赋值*/
dst.at<Vec3b>(row, col)[0] = saturate_cast<uchar>(b * alpha + beta);
dst.at<Vec3b>(row, col)[1] = saturate_cast<uchar>(g * alpha + beta);
dst.at<Vec3b>(row, col)[2] = saturate_cast<uchar>(r * alpha + beta);
}
}
}
imshow("src", src);
imshow("dst", dst);
waitKey(0);
return 0;
}
测试结果: