2021.3.27OpenCV05 Read and write image-pixel-modify pixel value-realize reverse color display-contrast image

/*
2021.3.27 txwtech
read and write images
Read and write pixels
Modify pixel value
imread You can specify to load as grayscale or RGB image
Imwrite to save image files, the type is determined by the extension.
Read the pixel value of a GRAY pixel (CV_8UC1)
Scalar intensity = img. at<uchar>(y, x);
or Scalar intensity = img.at<uchar>(Point(x, y));

Read the pixel value of an RGB pixel.
Vec3f intensity = img.at<Vec3f>(y, x);
float blue = intensity.val[0];
float green = intensity.val[1];
float red = intensity.val[ 2];

The sequence of Vec3b corresponding to the three channels is blue, green, red uchar type data.
Vec3f corresponds to three-channel float data.
Converting CV_8UC1 to CV32F1 is implemented as follows:
src.convertTo(dst, CV_32F);

//Move up and down the selected code, alt+arrow key

*/

/*
2021.3.27txwtech
读写图像
读写像素
修改像素值
imread 可以指定加载为灰度或者RGB图像
Imwrite 保存图像文件，类型由扩展名决定
读一个GRAY像素点的像素值（CV_8UC1）
Scalar intensity = img.at<uchar>(y, x);
或者 Scalar intensity = img.at<uchar>(Point(x, y));

读一个RGB像素点的像素值
Vec3f intensity = img.at<Vec3f>(y, x);
float blue = intensity.val[0];
float green = intensity.val[1];
float red = intensity.val[2];

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);

//对选中代码上下移动，alt+方向键

*/

#include <opencv2/opencv.hpp>
#include <iostream>

using namespace std;
using namespace cv;

int main(int argc, char *argv[])
{
	Mat src;
	Mat gray_src;
	src = imread("E:/pictures/test1.jpg");
	if (src.empty())
	{
		printf("cannot load image");
		return -1;
	}
	namedWindow("showpic",CV_WINDOW_AUTOSIZE);
	imshow("showpic",src);

	//转为灰度图像
	cvtColor(src,gray_src,CV_RGB2GRAY);//更改色彩空间
	namedWindow("gray_window", CV_WINDOW_AUTOSIZE);
	imshow("gray_window", gray_src);
	int height = gray_src.rows;
	int width = gray_src.cols;

	for(int row=0;row<height;row++)
	{ 
		for (int col = 0; col < width; col++)
		{ 
			int gray_value = gray_src.at<uchar>(row,col);
		//更改像素值-使之反色显示
		    gray_src.at<uchar>(row,col) = 255 - gray_value;
		}
	}
	namedWindow("灰度图像反差的图像",CV_WINDOW_AUTOSIZE);
	imshow("灰度图像反差的图像",gray_src);//显示更改后的图像
	
	//操作彩色图像
	Mat dst2;
	dst2.create(src.size(),src.type());
	height = src.rows;
	width = src.cols;
	int channelcount = src.channels();
	for (int row = 0; row < height; row++)
	{
		for (int col = 0; col < width; col++)
		{
			if (channelcount == 1)
			{
				int gray_value = gray_src.at<uchar>(row,col);
				gray_src.at<uchar>(row, col) = 255 - gray_value;
			}
			else if (channelcount == 3)//3通道表示彩色图像
			{
				/*int color_b = src.at<Vec3b>(row, col)[0];
				int color_g = src.at<Vec3b>(row, col)[1];
				int color_r = src.at<Vec3b>(row, col)[2];*/
				int color_b = src.at<Vec3b>(row, col)[0];
				int color_g = src.at<Vec3b>(row, col)[1];
				int color_r = src.at<Vec3b>(row, col)[2];
				//使彩色像素点反色
				dst2.at<Vec3b>(row, col)[0] = 255 - color_b;
				//dst2.at<Vec3b>(row, col)[0] = 0;//如果某一个通道都赋值为0，就会缺少一个色彩，
				dst2.at<Vec3b>(row, col)[1] = 255 - color_g;
				dst2.at<Vec3b>(row, col)[2] = 255 - color_r;

				//还可以3通道转单通道灰度图像
				//取最大像素点
				gray_src.at<uchar>(row, col) = max(color_r,max(color_b, color_g));
				取最小像素点
				//gray_src.at<uchar>(row, col) = min(color_r, min(color_b, color_g));
			}
		}
	}

	namedWindow("彩色图像反色显示",CV_WINDOW_AUTOSIZE);
	imshow("彩色图像反色显示", dst2);
	//API函数实现彩色反色相同效果
	Mat dst3;
	dst3.create(src.size(),src.type());
	bitwise_not(src,dst3);//通过位操作实现方法，求反差图片

	namedWindow("bitwise_not实现图像反色显示", CV_WINDOW_AUTOSIZE);
	imshow("bitwise_not实现图像反色显示", dst3);

	namedWindow("彩色转灰度取最大像素点", CV_WINDOW_AUTOSIZE);
	imshow("彩色转灰度取最大像素点", gray_src);

	waitKey(0);

	return 0;
}