讀讀一個GRAY畫素點的畫素值（CV_8UC1）

Scalar intensity = img.at<uchar>(y, x); 
或者 Scalar intensity = img.at<uchar>(Point(x, y));

讀一個RGB畫素點的畫素值
Vec3f intensity = img.at<Vec3f>(y, x); 
float blue = intensity.val[0]; 
float green = intensity.val[1]; 
float red = intensity.val[2];寫畫素

修改畫素值

灰度影象
img.at<uchar

Vec3b與Vec3F

Vec3b對應三通道的順序是blue、green、red的uchar型別資料。
Vec3f對應三通道的float型別資料
把CV_8UC1轉換到CV32F1實現如下：
src.convertTo(dst, CV_32F);

實現畫素取反的效果

程式碼：

#include <opencv2\opencv.hpp>

using namespace cv;
using namespace std;

int main()
{
	Mat src;
	src = imread("D:/opencvSRC/test.jpg");
	if (src.empty()) {

		printf("load image error!\n");
	}
	namedWindow("src", CV_WINDOW_AUTOSIZE);
	imshow("src", src);

	//單通道
	Mat dst1;
	cvtColor(src, dst1, CV_BGR2GRAY);
	int height = src.rows;
	int width = src.cols;
	int channels = src.channels();

	for (int row = 0; row < height; row++) {
		for (int col = 0; col < width; col++) {
			if (channels == 1) {

				int gray = dst1.at<uchar>(row, col);
				dst1.at<uchar>(row, col) = 255 - gray;
			}
		}
	}
	namedWindow("output1", CV_WINDOW_AUTOSIZE);
	imshow("output1", dst1);

	//三通道
	Mat dst;
	dst.create(src.size(), src.type());
	printf("height=%d width=%d channels=%d", height, width, channels);
	for (int row = 0; row < height; row++) {
		for (int col = 0; col < width; col++) {
			if (channels == 3) {
				int b = src.at<Vec3b>(row, col)[0];
				int g = src.at<Vec3b>(row, col)[1];
				int r = src.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;
			}
		}
	}
	namedWindow("output", CV_WINDOW_AUTOSIZE);
	imshow("output", dst);

	//一個函式解決
	Mat dst2;
	dst2.create(src.size(), src.type());

	bitwise_not(src, dst2);
	namedWindow("output2", CV_WINDOW_AUTOSIZE);
	imshow("output2", dst2);

	waitKey(0);
	return 0;
}
 

效果圖：