C++ Opencv 图片运算和处理

色彩空间

RGB 和 BGR

opencv主要使用BGR，与其他显示设备RGB不同需注意，是产生颜色不对的原因所在。
opencv Mat的type()值参照表

-	C1	C2	1C3	C4	C(5)	C(6)	C(7)	C(8)
CV_8U	0	8	16	24	32	40	48	56
CV_8S	1	9	17	25	33	41	49	57
CV_16U	2	10	18	26	34	42	50	58
CV_16S	3	11	19	27	35	43	51	59
CV_32S	4	12	20	28	36	44	52	60
CV_32F	5	13	21	29	37	45	53	61
CV_64F	6	14	22	30	38	46	54	62

HSV 和 HSL

HSV：H（Hue）表示色相，S（saturation）表示饱和度，V（value）明度

HSL：H（Hue）表示色相，S（saturation）表示饱和度，L（lightness）亮度

YUV

YUV：主要用于视频处理，数据源Y代表灰色图像，U、V代表颜色

YUV4:2:0 表示没4个Y里，要么有2个U，要么有2个V

划线

#include <iostream>
#include <vector>
#include <opencv2/core.hpp>
#include <opencv2/highgui.hpp>
#include <opencv2/imgcodecs.hpp>
#include <opencv2/video.hpp>
#include <NumCpp.hpp>

cv::Mat array2Img(nc::NdArray<uchar> array);

void main(){
   
	nc::NdArray<uchar> img_array = nc::NdArray<uchar>(40, 60);
   img_array.zeros();
    cv::Mat line_img;
    int count = 0;
    while (count < 30) {
   
        img_array(count ,9) = 255;      // blue
        img_array(count, 10) = 255;     // green
        img_array(count, 11) = 255;     // red
        count += 1;
    }
    for (size_t i = 0; i < img_array.numRows(); i++)
    {
   
        std::cout << "第" << i << ": ";
        for (size_t j = 0; j < img_array.numCols(); j++)
        {
   
            std::cout << (size_t)img_array(i, j);
        }
        std::cout << "\n";
    }
    line_img = array2Img(img_array);
    cv::namedWindow("line_img", cv::WINDOW_NORMAL);
    cv::imshow("line_img",line_img);
    cv::waitKey(0);
 }
 //数组转图片
cv::Mat array2Img(nc::NdArray<uchar> array) {
   
    
    size_t h = array.numRows();
    size_t w = array.numCols();

    cv::Mat img(h,(size_t)(w/3), CV_8UC3);     //保存为RGB
    for (size_t i = 0; i < h; i++)
    {
   
        uchar* tmp = img.ptr<uchar>(i);
        for (size_t j = 0; j < w; j++)
        {
   
            tmp[j] = array(i, j);
        }
    }
    return img;
}

3通道分割和合并

方法一

	std::vector<cv::Mat> channelsSplistArray, channelsMergeArray;
    cv::Mat buleChannel, redChannel, greenChannel,newAddchannel,imgMerge;
    //分割, 相应通道颜色的会转为灰色
    cv::split(line_img, channelsSplistArray);    // &
    buleChannel = channelsSplistArray.at(0);     // 0   255 255
    greenChannel = channelsSplistArray.at(1);    // 255 0   255 
    redChannel = channelsSplistArray.at(2);      // 255 255 0
    cv::imshow("buleChannel", buleChannel);
    cv::imshow("greenChannel", greenChannel);
    cv::imshow("redChannel", redChannel);
    // 合并三通道 设置blue为0
    newAddchannel = channelsSplistArray.at(0).clone();
    newAddchannel.setTo(0);
    channelsMergeArray.push_back(newAddchannel);
    channelsMergeArray.push_back(greenChannel);
    channelsMergeArray.push_back(redChannel);
    cv::merge(channelsMergeArray, imgMerge);
    // 当通道设置为0 ： 0为blue 1为green 2为red
    /*channelsSplistArray[0] = cv::Scalar(0);      
    cv::merge(channelsSplistArray, imgMerge);*/
    cv::imshow("imgMerge", imgMerge);

方法二

    cv::Mat newAddchannel, imgMerge, imgChannelSplitArray[3];
    // 分割
    cv::split(line_img, imgChannelSplitArray)