分离RGB彩图颜色通道 也就是把每种分量的亮度图提出来

vector<Mat> channels;split(image1, channels);Mat R = channels.at(0);Mat G = channels.at(1);Mat B = channels.at(2);

这样R,G,B每个图就是这个图的颜色分量图了

图片的克隆，深拷贝！

Mat image1_copy = image1.clone();

申明一个点操作

Point pt;pt.x = 10;pt.y = 10;

这样就可以得到一个点，你可以把它当作圆心来进行画圆操作

circle(image1_copy,pt, 6, CV_RGB(255, 0, 0), -1, 8, 0);

图，点，半径，颜色，-1代表填充1代表不填充，8和0都是默认参数

也可以申明两个点，进行画线操作。

line(image1_copy, Point(20,20), pt2, CV_RGB(0, 255, 0), 1, 8, 0);

这里也可以直接在函数里面写Point(20,20)也代表了一个点，但就不能在其他地方用这个了。

申明一个矩形的操作，也可以叫矩形的ROI

Rect rect;rect.x = 10;rect.y = 10;rect.width = 90;rect.height = 90;rectangle(image1_copy, rect, CV_RGB(243, 125, 254), 1, 8, 0);

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下面是直方图统计图的画法

统计各个通道的RGB函数 网上的学习

void showHist(Mat& img, Mat& dst)
{//1、创建3个矩阵来处理每个通道输入图像通道。//我们用向量类型变量来存储每个通道，并用split函数将输入图像划分成3个通道。vector<Mat>bgr;split(img, bgr);//2、定义直方图的区间数int numbers = 256;//3、定义变量范围并创建3个矩阵来存储每个直方图float range[] = { 0,256 };const float* histRange = { range };Mat b_hist, g_hist, r_hist;//4、使用calcHist函数计算直方图int numbins = 256;calcHist(&bgr[0], 1, 0, Mat(), b_hist, 1, &numbins, &histRange);calcHist(&bgr[1], 1, 0, Mat(), g_hist, 1, &numbins, &histRange);calcHist(&bgr[2], 1, 0, Mat(), r_hist, 1, &numbins, &histRange);//5、创建一个512*300像素大小的彩色图像，用于绘制显示int width = 800;int height = 600;Mat histImage(height, width, CV_8UC3, Scalar(0, 0, 0));//6、将最小值与最大值标准化直方图矩阵normalize(b_hist, b_hist, 0, height, NORM_MINMAX);normalize(g_hist, g_hist, 0, height, NORM_MINMAX);normalize(r_hist, r_hist, 0, height, NORM_MINMAX);//7、使用彩色通道绘制直方图int binStep = cvRound((float)width / (float)numbins);  //通过将宽度除以区间数来计算binStep变量for (int i = 1; i < numbins; i++){line(histImage,Point(binStep * (i - 1), height - cvRound(b_hist.at<float>(i - 1))),Point(binStep * (i), height - cvRound(b_hist.at<float>(i))),Scalar(255, 0, 0));line(histImage,Point(binStep * (i - 1), height - cvRound(g_hist.at<float>(i - 1))),Point(binStep * (i), height - cvRound(g_hist.at<float>(i))),Scalar(0, 255, 0));line(histImage,Point(binStep * (i - 1), height - cvRound(r_hist.at<float>(i - 1))),Point(binStep * (i), height - cvRound(r_hist.at<float>(i))),Scalar(0, 0, 255));}dst = histImage;return;
}

其中值得学习的函数有：

创建画布：

int width = 800;int height = 600;Mat histImage(height, width, CV_8UC3, Scalar(0, 0, 0));

归一化高度宽度

normalize(b_hist, b_hist, 0, height, NORM_MINMAX);normalize(g_hist, g_hist, 0, height, NORM_MINMAX);normalize(r_hist, r_hist, 0, height, NORM_MINMAX);

对直方图函数处理后的每个统计直方图大小的处理

height - cvRound(b_hist.at<float>(i - 1)

因为画布是从上往下数的

计算灰度图的直方统计量函数

int numbers = 256;//3、定义变量范围并创建3个矩阵来存储每个直方图float range[] = { 0,256 };const float* histRange = { range };Mat b_hist, g_hist, r_hist;//4、使用calcHist函数计算直方图int numbins = 256;calcHist(&bgr[0], 1, 0, Mat(), b_hist, 1, &numbins, &histRange);calcHist(&bgr[1], 1, 0, Mat(), g_hist, 1, &numbins, &histRange);calcHist(&bgr[2], 1, 0, Mat(), r_hist, 1, &numbins, &histRange);

统计各个通道的RGB函数 自己的编写

int h = R.rows;int w = R.cols;int hisgramR[256] = {0};for (int j = 0; j < h; j++) {for (int i = 0; i < w; i++) {hisgramR[R.at<uchar>(j, i)]= hisgramR[R.at<uchar>(j, i)]+1;}}

针对于每个像素进行统计

int nHistWidth = 256;int nHistHeight =400;Mat matHistImage(nHistHeight, nHistWidth, CV_8UC3, Scalar(255, 255, 255));for (int i = 0; i < 256; i++) {line(matHistImage, Point(i, nHistHeight-1), Point(i, nHistHeight-hisgramR[i]*400/5000), CV_RGB(255,0, 0), 1, 8, 0);}

制造画布，且归一化可能不太标准，找了一个比较大的数进行相乘除