C语言实现RGB图像转换成灰（Gray）度图像

以前实现RGB图像转换成灰度图像都是直接调用OpenCV的库函数RGB2GRAY(IplImage* src);最近老板让我们除了读入输出图像实时用OpenCV的函数，其余的最好都是自己写，所以我自己上网查了一些资料，得到了一些转换算法，并且用c语言实现，具体归纳下来有如下三种：

方法一.对于RGB转灰度，有一个很著名的心理公式：Gray = r*0.299 + g*0.587 + b*0.114;

方法二.Adobephotoshop的公式：Adobe RGB(1998)[gamma = 2.20], gray = (r^2.2 * 0.2973 + g^2.2 * 0.6274 + b^2.2 * 0.0753)^(1/2.2);

方法三.平均值：gray = (r + b + r) / 3;

具体代码如下：

/*****************************************************************************************************
 *	File name: RGB2Gray.cpp
 *	Author: source code by RamiYim
 *	Version: cs-hhu-cn0.0
 *	Date: 2014.11.13
 *	Description: read a RGB frame, change it to Gray.
 *	Others:
 *	Function List: main functions and its function
 *	History: ,<20141113>,,
******************************************************************************************************/
#include "RGB2Gray.h"
#include "cv.h"
#include "highgui.h"
#include "math.h"
#include 

void RGB2GrayTypical(int sizeOfPixel, char *imageData);
void RGB2GrayInPhotoShop(int sizeOfPixel, char *imageData);
void RGB2GrayAverage(int sizeOfPixel, char *imageData);

char *gray;			//用于存放转换后的灰度像素值

void main(){
	IplImage *srcImage = cvLoadImage("D:\\testdata\\lena.jpg");
	cvShowImage("srcImage", srcImage);
	int width = srcImage->width;			//图像宽度
	int height = srcImage->height;		//图像高度
	int nChannels = srcImage->nChannels;	//通道数
	int sizeOfPixel = width * height;		//像素数
	IplImage *grayImage = cvCreateImage(cvSize(width, height), IPL_DEPTH_8U, 1);//创建灰度图像
	gray = (char *) malloc(sizeof(char) * width * height);			//灰度图像的＂imageData＂初始化
	RGB2GrayTypical(sizeOfPixel, srcImage->imageData);				//转换成gray图像
	grayImage->imageData = gray;
	cvShowImage("grayImageTypical", grayImage);

	RGB2GrayInPhotoShop(sizeOfPixel, srcImage->imageData);				//转换成gray图像
	grayImage->imageData = gray;
	cvShowImage("RGB2GrayInPhotoShop", grayImage);

	RGB2GrayAverage(sizeOfPixel, srcImage->imageData);
	grayImage->imageData = gray;
	cvShowImage("RGB2GrayAverage", grayImage);

	cvWaitKey();
}


/******************************************************************************************************
 *	Function:RGB2GrayTypical()
 *	Description：输入一帧RGB图像，得到其灰度图像
 *	Calls://none
 *	Called by：//main
 *	Input：//none
 *	Output：//none
 *	Return://void
 *	Others：//算法思想：Gray = R*0.299 + G*0.587 + B*0.114
 *	History: ,<20141113>,,
 ******************************************************************************************************/
void RGB2GrayTypical(int sizeOfPixel, char *imageData){
	for (int i = 0; i < sizeOfPixel; i++)
	{
		uchar b = (uchar)imageData[3 * i + 0];
		uchar g = (uchar)imageData[3 * i + 1];
		uchar r = (uchar)imageData[3 * i + 2];
		gray[i] = r * 0.299 + g * 0.587 + b * 0.114;
	}
}


/******************************************************************************************************
 *	Function:RGB2GrayInPhotoShop()
 *	Description：输入一帧RGB图像，得到其灰度图像
 *	Calls://none
 *	Called by：//main
 *	Input：//none
 *	Output：//none
 *	Return://void
 *	Others：//算法思想：Gray = (R^2.2 * 0.2973 + G^2.2 * 0.6274 + B^2.2 * 0.0753)^(1/2.2)
 *	History: ,<20141114>,,
 ******************************************************************************************************/
void RGB2GrayInPhotoShop(int sizeOfPixel, char *imageData){
	for (int i = 0; i < sizeOfPixel; i++)
	{
		uchar b = imageData[3 * i + 0];
		uchar g = imageData[3 * i + 1];
		uchar r = imageData[3 * i + 2];
		gray[i] = pow((pow(r, 2.2) * 0.2973 + pow(g, 2.2) * 0.6274 + pow(b, 2.2) * 0.0753), 1/2.2);
	}
}


/******************************************************************************************************
 *	Function:RGB2GrayAverage()
 *	Description：输入一帧RGB图像，通过均值法得到其灰度图像
 *	Calls://none
 *	Called by：//main
 *	Input：//none
 *	Output：//none
 *	Return://void
 *	Others：//算法思想：gray = (r + g + b) / 3
 *	History: ,<20141114>,,
 ******************************************************************************************************/
void RGB2GrayAverage(int sizeOfPixel, char *imageData){
	for (int i = 0; i < sizeOfPixel; i++)
	{
		uchar b = imageData[3 * i + 0];
		uchar g = imageData[3 * i + 1];
		uchar r = imageData[3 * i + 2];
		gray[i] = (b + g + r) / 3;
	}
}

输出结果如下：