使用OpenCV实现RGB、HSI、CMYK颜色空间的转换

RGB to HSI、CMYK的代码实现

前言：

在之前博文的基础上，我使用OpenCV2实现了RGB颜色空间向HIS、CMYK转换的代码。下列链接为各种经典颜色空间的介绍及转换公式的介绍。

http://blog.youkuaiyun.com/solomon1558/article/details/43772147

1. RGB to HIS

    HSI与RGB颜色空间可以进行相互转换。RGB转换到HSI 的计算公式如下：首先给定RGB颜色空间的值(R,G,B),其中R,G,B∈[ 0,2 5 5]，则转换到HSI  空间的(H,S,I)值的计算如下：设将(R ,G ,B)归一化得(R',G',B')为：

 

int rgb2hsi(Mat &image,Mat &hsi){
	if(!image.data){
		cout<<"Miss Data"<<endl;
		return -1;
	}
	int nl = image.rows;
	int nc = image.cols;
	if(image.isContinuous()){
		nc = nc*nl;
		nl = 1;
	}
	for(int i = 0;i < nl;i++){
		uchar *src = image.ptr<uchar>(i);
		uchar *dst = hsi.ptr<uchar>(i);
		for(int j = 0;j < nc;j++){
			float b = src[j*3]/255.0;
			float g = src[j*3+1]/255.0;
			float r = src[j*3+2]/255.0;
			float num = (float)(0.5*((r-g)+(r-b)));
			float den = (float)sqrt((r-g)*(r-g)+(r-b)*(g-b));
			float H,S,I;
			if(den == 0){	//分母不能为0
				H = 0;
			}
			else{
				double theta = acos(num/den);
				if(b <= g)
					H = theta/(PI*2);
				else
					H = (2*PI - theta)/(2*PI);
			}
			double minRGB = min(min(r,g),b);
			den = r+g+b;
			if(den == 0)	//分母不能为0
				S = 0;
			else
				S = 1 - 3*minRGB/den;
			I = den/3.0;
			//将S分量和H分量都扩充到[0,255]区间以便于显示;
			//一般H分量在[0,2pi]之间，S在[0,1]之间
			dst[3*j] = H*255;
			dst[3*j+1] = S*255;
			dst[3*j+2] = I*255;
		}
	}
	return 0;
}

【注】：

    程序中将S分量和H分量都扩充到[0,255]区间以便于显示;

    一般H分量在[0,2pi]之间，S在[0,1]之间。

2.   RGB to CMYK

    给定RGB颜色空间的值(R,G,B)，其中R,G ,B∈ [0, 2 5 5]，则转换到CMYK 空间的(C,M,Y,K)值的计算如下：

 

【注】式中，maxG是每个矢量分量的最大允许值(255)；C , M , Y , K ∈ [ 0,255]。

int rgb2cmyk( Mat &image,Mat &cmyk){
	if(!image.data){
		cout<<"Miss Data"<<endl;
		return -1;
	}
	int nl = image.rows;	//行数
	int nc = image.cols;	//列数
	if(image.isContinuous()){	//没有额外的填补像素
		nc = nc*nl;
		nl = 1;					//It is now a 1D array
	}
	//对于连续图像，本循环只执行1次
	for(int i=0;i<nl;i++){
		uchar *data = image.ptr<uchar>(i);
		uchar *dataCMYK = cmyk.ptr<uchar>(i);
		for(int j = 0;j < nc;j++){
			uchar b = data[3*j];
			uchar g = data[3*j+1];
			uchar r = data[3*j+2];
			uchar c = 255 - r;
			uchar m = 255 - g;
			uchar y = 255 - b;
			uchar k = min(min(c,m),y);
			dataCMYK[4*j] = c - k;
			dataCMYK[4*j+1] = m  - k;
			dataCMYK[4*j+2] = y  - k;
			dataCMYK[4*j+3] = k;
		}
	}
	return 0;
}

3. 完整的工程

#include<opencv2\core\core.hpp>
#include<opencv2\highgui\highgui.hpp>
#include<opencv2\opencv.hpp>
#include<vector>
#define PI 3.1416
#define min(a,b) (a<b?a:b)
using namespace std;
using namespace cv;

int rgb2hsi(Mat &image,Mat &hsi){
	if(!image.data){
		cout<<"Miss Data"<<endl;
		return -1;
	}
	int nl = image.rows;
	int nc = image.cols;
	if(image.isContinuous()){
		nc = nc*nl;
		nl = 1;
	}
	for(int i = 0;i < nl;i++){
		uchar *src = image.ptr<uchar>(i);
		uchar *dst = hsi.ptr<uchar>(i);
		for(int j = 0;j < nc;j++){
			float b = src[j*3]/255.0;
			float g = src[j*3+1]/255.0;
			float r = src[j*3+2]/255.0;
			float num = (float)(0.5*((r-g)+(r-b)));
			float den = (float)sqrt((r-g)*(r-g)+(r-b)*(g-b));
			float H,S,I;
			if(den == 0){	//分母不能为0
				H = 0;
			}
			else{
				double theta = acos(num/den);
				if(b <= g)
					H = theta/(PI*2);
				else
					H = (2*PI - theta)/(2*PI);
			}
			double minRGB = min(min(r,g),b);
			den = r+g+b;
			if(den == 0)	//分母不能为0
				S = 0;
			else
				S = 1 - 3*minRGB/den;
			I = den/3.0;
			//将S分量和H分量都扩充到[0,255]区间以便于显示;
			//一般H分量在[0,2pi]之间，S在[0,1]之间
			dst[3*j] = H*255;
			dst[3*j+1] = S*255;
			dst[3*j+2] = I*255;
		}
	}
	return 0;
}

int rgb2cmyk( Mat &image,Mat &cmyk){
	if(!image.data){
		cout<<"Miss Data"<<endl;
		return -1;
	}
	int nl = image.rows;	//行数
	int nc = image.cols;	//列数
	if(image.isContinuous()){	//没有额外的填补像素
		nc = nc*nl;
		nl = 1;					//It is now a 1D array
	}
	//对于连续图像，本循环只执行1次
	for(int i=0;i<nl;i++){
		uchar *data = image.ptr<uchar>(i);
		uchar *dataCMYK = cmyk.ptr<uchar>(i);
		for(int j = 0;j < nc;j++){
			uchar b = data[3*j];
			uchar g = data[3*j+1];
			uchar r = data[3*j+2];
			uchar c = 255 - r;
			uchar m = 255 - g;
			uchar y = 255 - b;
			uchar k = min(min(c,m),y);
			dataCMYK[4*j] = c - k;
			dataCMYK[4*j+1] = m  - k;
			dataCMYK[4*j+2] = y  - k;
			dataCMYK[4*j+3] = k;
		}
	}
	return 0;
}
int main(){
	Mat img = imread("E:\\CV视频处理工作室\\Test_Photo\\lena_1.jpg");
	if(!img.data){
		cout<<"Miss Data"<<endl;
		return -1;
	}
	Mat img_cmyk,img_hsi;
	Mat img_hsv;
	vector <Mat> vecRgb,vecHsi,vecHls,vecHsv,vecCmyk;
	img_hsv.create(img.rows,img.cols,CV_8UC3);
	Mat img_hls;
	img_hls.create(img.rows,img.cols,CV_8UC3);
	//生成与输入图像尺寸一样的4通道cmyk图像
	img_cmyk.create(img.rows,img.cols,CV_8UC4);
	img_hsi.create(img.rows,img.cols,CV_8UC3);
	rgb2cmyk(img,img_cmyk);
	rgb2hsi(img,img_hsi);
	cvtColor(img,img_hsv,CV_BGR2HSV);
	cvtColor(img,img_hls,CV_BGR2HLS);
	split(img_cmyk,vecCmyk);
	split(img_hsi,vecHsi);
	cout<<"pixel(0,0) in RGB"<<endl;
	for(int i=0;i<3;i++){
		cout<<(int)img.at<Vec3b>(0,0)[i]<<" ";
	}
	cout<<endl<<"pixel(0,0) in CMYK"<<endl;
	for(int i=0;i<4;i++){
		cout<<(int)img_cmyk.at<Vec4b>(0,0)[i]<<" ";
	}
	int a = min(min(24,32),16);
	cout<<endl<<a;
	namedWindow("RGB_Image");
	namedWindow("CMYK_Image");
	//namedWindow("HSV_Image");
	//namedWindow("HLS_Image");
	namedWindow("HSI_Image");
	namedWindow("CMYK_C");
	namedWindow("CMYK_M");
	namedWindow("CMYK_Y");
	namedWindow("CMYK_K");
	imshow("CMYK_C",vecCmyk[0]);
	imshow("CMYK_M",vecCmyk[1]);
	imshow("CMYK_Y",vecCmyk[2]);
	imshow("CMYK_K",vecCmyk[3]);
	imshow("HSI_H",vecHsi[0]);
	imshow("HSI_S",vecHsi[1]);
	imshow("HSI_I",vecHsi[2]);
	imshow("RGB_Image",img);
	imshow("CMYK_Image",img_cmyk);
	//imshow("HSV_Image",img_hsv);
	//imshow("HLS_Image",img_hls);
	imshow("HSI_Image",img_hsi);
	waitKey();
	return 0;
}