少有人走的路修改像素值
灰度图像
img.at< uchar>(y,x) = 128;
RGB三通道图像
img.at< Vec3b>(y,x)[0]=128;//blue
img.at< Vec3b>(y,x)[1]=128;//blue
img.at< Vec3b>(y,x)[2]=128;//blue
空白图像
img=Scalar(0);
ROI选择
Rect r(10,10,100,100);
Mat smalling=img(r);
Vec3b与Vec3F
Vec3b对应三通道的顺序是blue、green、red的uchar类型数据
Vec3f对应三通道的float类型数据
把CV_8UC1转换到CV32F1实现如下:
src.convertTo(dst,CV_32F);
实例程序：
#include<iostream>
#include<opencv2/core/core.hpp>
#include<highgui/highgui.hpp>
#include <opencv2/imgproc/imgproc.hpp>
using namespace cv;
using namespace std;
int main()
{
Mat img = imread("1.jpg");
if(img.empty())
{
cout << "Image Load Failed"<< endl;
//system("pause");
return -1;
}
namedWindow("MyWindow2", CV_WINDOW_AUTOSIZE);
imshow("MyWindow2", img);
Mat gray_img;
cvtColor(img,gray_img,CV_BGR2GRAY);
int height = gray_img.rows;
int width = gray_img.cols;
namedWindow("output",WINDOW_AUTOSIZE);
imshow("output",gray_img);
//单通道的像素操作
for(int row = 0;row<height;row++)
{
for(int col = 0;col<width;col++)
{
int gray = gray_img.at<uchar>(row,col);
gray_img.at<uchar>(row,col) = 255 -gray;
}
}
imshow("output2",gray_img);
Mat dst;
dst.create(img.size(),img.type());
height = dst.rows;
width = dst.cols;
int cn = dst.channels();
for(int row = 0;row<height;row++){
for(int col = 0;col < width;col++){
if(cn == 1)
{
}
else if(cn == 3){ //彩色图像的反差处理
int b = img.at<Vec3b>(row,col)[0];
int g = img.at<Vec3b>(row,col)[1];
int r = img.at<Vec3b>(row,col)[2];
dst.at<Vec3b>(row,col)[0] = 255 -b;
dst.at<Vec3b>(row,col)[1] = 255 -g;
dst.at<Vec3b>(row,col)[2] = 255 -r;
}
}
}
imshow("output4",dst);
Mat outimg;
bitwise_not(img,outimg);
imshow("output5",outimg);
waitKey(0);
return 0;
}效果:
源码和原图片请到Github下载:
https://github.com/MRwangmaomao/OpencvPixel-Project.git
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版权声明：本文为CSDN博主「南山二毛」的原创文章，遵循 CC 4.0 BY-SA 版权协议，转载请附上原文出处链接及本声明。
原文链接：https://blog.csdn.net/qq_16481211/article/details/79561262
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