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BBHE算法

yoyo2
2018-03-04 00:57:43
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function BBHE2
%UNTITLED 此处显示有关此函数的摘要
%   此处显示详细说明
 clc;  
 clear all  
 close all;  
I0=imread('E:\图像处理数据\ceshi\ceshi5(0).jpg');                 %读入JPG彩色图像文件  


if size(I0,3)==3  
    I=rgb2gray(I0);  
else   
    I=I0;  
end  
% figure,imshow(I);  
% title('灰度图')  
 meanv=floor(mean(I(:)));  
[m,n]=size(I);  %测量图像尺寸参数  
pl=zeros(1,meanv);     
pu=zeros(1,256);%预创建存放灰度出现概率的向量  
nl=0;  
nu=0;  
for i=1:m  
    for j=1:n  
        if I(i,j)<meanv  
            pl(I(i,j) + 1) = pl(I(i,j) + 1)  + 1;  
            nl=nl+1;  
        else  
            pu(I(i,j)+1)=pu(I(i,j)+1)+1;  
            nu=nu+1;  
        end  
    end  
end  
pl=pl./nl;  
pu=pu./nu;  
cl=zeros(1,meanv+1);  
cu=zeros(1,256);  
cl(1)=pl(1);  
cu(meanv+1)=pu(meanv+1);  
for i=2:meanv  
     cl(i)=pl(i) + cl(i-1); %统计图像中<每个灰度级像素的累积个数,s(i):0,1,```,i-1  
end  
for i=meanv+2:256  
    cu(i)=pu(i)+cu(i-1);  
end  
for i=1:meanv  
    cl(i)=cl(i)*meanv;     
end  
for i=meanv+1:256  
    cu(i)=meanv+1+cu(i)*(256-meanv);  
end  
%图像均衡化  
I_equal = I;  
for i=1:m  
    for j=1:n  
        if I(i,j)<meanv  
           I_equal(i,j) = cl( I(i,j) + 1);  
        else  
            I_equal(i,j)=cu(I(i,j)+1);  
        end  
    end  
end  
pic=I_equal;  
%figure,imshow(I_equal);
 imshow(I_equal,'border','tight','initialmagnification','fit');
set (gcf,'Position',[0,0,1000,625]);
axis normal;
figure;
subplot(221);  
imshow(I);
subplot(223); 
imhist(I);
subplot(222);  
imshow(I_equal);
subplot(224); 
imhist(I_equal);
%显示均衡化后的图像   
% title('均衡化后图像')  
%   
% q=zeros(1,256);                            %预创建存放灰度出现概率的向量  
% for i=1:m  
%     for j=1:n  
%      q(I_equal(i,j) + 1) = q(I_equal(i,j) + 1)  + 1;  
%     end  
% end  
% q=q/(m*n);  
% x=0:255;  
% figure(3);  
% plot(x,q,'g');  


end


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BBHE算法 (42.68 kB)

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