#include<iostream>
#include<opencv2/opencv.hpp> using namespace std;
using namespace cv; int main(int argc, char **argv)
{
Mat src = imread("D:/meinv.jpg");
namedWindow("源图像",CV_WINDOW_AUTOSIZE);
imshow("源图像",src);
/*Mat gray;
cvtColor(src, gray, CV_BGR2GRAY);
imshow("灰度图像", gray);*/
/* 对灰度图像的像素改写
int height = src.rows;
int width = src.cols;
int channels = src.channels();
for (int i = 0; i < height; i++)
{
for (int j = 0; j < width; j++)
{
int gray_data = gray.at<uchar>(i, j);
gray.at<uchar>(i, j) = 255 - gray_data;
}
}
imshow("反色图像", gray);*/
}
显示结果:
(1)彩色图像
(2)灰度图像
(3)反色图像
2.对彩色图像像素的操作
Mat dst;
dst.create(src.size(), src.type());
int height = src.rows;
int width = src.cols;
int channels = src.channels(); for (int i = 0; i < height; i++)
{
for (int j = 0; j < width; j++)
{
int b = src.at<Vec3b>(i, j)[0];
int g = src.at<Vec3b>(i, j)[1];
int r = src.at<Vec3b>(i, j)[2]; dst.at<Vec3b>(i, j)[0] = 255 - b;
dst.at<Vec3b>(i, j)[1] = 255 - g;
dst.at<Vec3b>(i, j)[2] = 255 - r;
}
}
//进行反色的另一种方法:调用API
/*bitwise_not(src, dst);*/
imshow("反色图像",dst);
imwrite("D:/dst.jpg", dst);
waitKey(0);
return 0;
显示结果: