【图像处理】彩色直方图均衡

sourcePic=imread('D:Imagespic_loc1870358810205041517.jpg');
[m,n,o]=size(sourcePic);
grayPic=rgb2gray(sourcePic);
figure,imshow(sourcePic);
figure,imshow(grayPic);
 
gp=zeros(1,256); %计算各灰度出现的概率
for i=1:256
	gp(i)=length(find(grayPic==(i-1)))/(m*n);
end
figure,bar(0:255,gp);
title('原图像直方图');
xlabel('灰度值');
ylabel('出现概率');
 
newGp=zeros(1,256); %计算新的各灰度出现的概率
S1=zeros(1,256);
S2=zeros(1,256);
tmp=0;
for i=1:256
	tmp=tmp+gp(i);
	S1(i)=tmp;
	S2(i)=round(S1(i)*256);
end
for i=1:256
	newGp(i)=sum(gp(find(S2==i)));
end
figure,bar(0:255,newGp);
title('均衡化后的直方图');
xlabel('灰度值');
ylabel('出现概率');
 
newGrayPic=grayPic; %填充各像素点新的灰度值
for i=1:256
	newGrayPic(find(grayPic==(i-1)))=S2(i);
end
figure,imshow(newGrayPic);

结果：

当然，有时候我们不禁想得到一幅图的灰度直方图均衡化结果，而是希望得到彩色图均衡化结果，那么就需要先将彩色图分为RGB分量，代码如下：

sourcePic=imread('D:Imagespic_loc1870358810205041517.jpg');
[m,n,o]=size(sourcePic);
figure,imshow(sourcePic,[]);
%grayPic=rgb2gray(sourcePic);
grayPic=sourcePic(:,:,1);
 
gp=zeros(1,256); %计算各灰度出现的概率
for i=1:256
	gp(i)=length(find(grayPic==(i-1)))/(m*n);
end
 
newGp=zeros(1,256); %计算新的各灰度出现的概率
S1=zeros(1,256);
S2=zeros(1,256);
tmp=0;
for i=1:256
	tmp=tmp+gp(i);
	S1(i)=tmp;
	S2(i)=round(S1(i)*256);
end
for i=1:256
	newGp(i)=sum(gp(find(S2==i)));
end
 
newGrayPic=grayPic; %填充各像素点新的灰度值
for i=1:256
	newGrayPic(find(grayPic==(i-1)))=S2(i);
end
nr=newGrayPic;
 
 
grayPic=sourcePic(:,:,2);
 
gp=zeros(1,256); %计算各灰度出现的概率
for i=1:256
	gp(i)=length(find(grayPic==(i-1)))/(m*n);
end
 
newGp=zeros(1,256); %计算新的各灰度出现的概率
S1=zeros(1,256);
S2=zeros(1,256);
tmp=0;
for i=1:256
	tmp=tmp+gp(i);
	S1(i)=tmp;
	S2(i)=round(S1(i)*256);
end
for i=1:256
	newGp(i)=sum(gp(find(S2==i)));
end
 
newGrayPic=grayPic; %填充各像素点新的灰度值
for i=1:256
	newGrayPic(find(grayPic==(i-1)))=S2(i);
end
ng=newGrayPic;
 
 
 
grayPic=sourcePic(:,:,3);
 
gp=zeros(1,256); %计算各灰度出现的概率
for i=1:256
	gp(i)=length(find(grayPic==(i-1)))/(m*n);
end
 
newGp=zeros(1,256); %计算新的各灰度出现的概率
S1=zeros(1,256);
S2=zeros(1,256);
tmp=0;
for i=1:256
	tmp=tmp+gp(i);
	S1(i)=tmp;
	S2(i)=round(S1(i)*256);
end
for i=1:256
	newGp(i)=sum(gp(find(S2==i)));
end
 
newGrayPic=grayPic; %填充各像素点新的灰度值
for i=1:256
	newGrayPic(find(grayPic==(i-1)))=S2(i);
end
nb=newGrayPic;
 
 
res=cat(3,nr,ng,nb);
figure,imshow(res,[]);

结果：

从原博客评论看，博主的方法是有问题的，不应该在RGB分开均衡，而应该在HSV上执行，否则存在严重的失真。

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