I=imread('0294.jpg'); I=imresize(I,[300 300]); I1=RGB2Lab(I); L1 = double(I1(:,:,1)); L2 = double(I1(:,:,2)); L3 = double(I1(:,:,3)); PL1=mean(L1(:)); PL2=mean(L2(:)); PL3=mean(L3(:)); [m,n]=size(L1); for i=1:m for j=1:n LL1(i,j)=abs(L1(i,j)-PL1); end end for i=1:m for j=1:n LL2(i,j)=abs(L2(i,j)-PL2); end end for i=1:m for j=1:n LL3(i,j)=abs(L3(i,j)-PL3); end end LLL1=reshape(LL1,1,[]); SL1=std(LLL1); LLL2=reshape(LL2,1,[]); SL2=std(LLL2); LLL3=reshape(LL3,1,[]); SL3=std(LLL3); %比较标准差最大 SL=max(max(SL1,SL2),SL3); G = fspecial('gaussian', [5 5], 1); GL1=imfilter(LL1, G, 'circular'); hist=imhist(GL1)/prod(size(GL1)); G1=find(hist); H1=-hist(G1)'*log2(hist(G1)); GL2=imfilter(LL2, G, 'circular'); hist=imhist(GL2)/prod(size(GL2)); G2=find(hist); H2=-hist(G2)'*log2(hist(G2)); GL3=imfilter(LL3, G, 'circular'); hist=imhist(GL3)/prod(size(GL3)); G3=find(hist); H3=-hist(G3)'*log2(hist(G3)); %比较二维熵最小的 H=min(min(H1,H2),H3); if(SL==SL1) ZL=LL1; end if(SL==SL2) ZL=LL2; end if(SL==SL3) ZL=LL3; end if(H==H1) HL=LL1; end if(H==H2) HL=LL2; end if(H==H3) HL=LL3; end %计算初始显著图 C=0.35*ZL+0.65*HL; [Z E]=lrr(C,0.01);%全局低秩Z为低秩部分E为稀疏部分 ZZ=(C-Z).*C; figure,imshow(ZZ,[]);如何调整代码使其在处理图片时最终输出的图片不会改变大小

您可以将imresize函数中的大小参数改为原图像的大小，即：

I=imread('0294.jpg'); 
I1=RGB2Lab(I); 
L1 = double(I1(:,:,1));  
L2 = double(I1(:,:,2)); 
L3 = double(I1(:,:,3)); 
PL1=mean(L1(:)); 
PL2=mean(L2(:)); 
PL3=mean(L3(:)); 
[m,n]=size(L1); 
for i=1:m 
    for j=1:n 
        LL1(i,j)=abs(L1(i,j)-PL1); 
    end 
end   
for i=1:m 
    for j=1:n 
        LL2(i,j)=abs(L2(i,j)-PL2); 
    end 
end   
for i=1:m 
    for j=1:n 
        LL3(i,j)=abs(L3(i,j)-PL3); 
    end 
end  
LLL1=reshape(LL1,1,[]); 
SL1=std(LLL1); 
LLL2=reshape(LL2,1,[]); 
SL2=std(LLL2); 
LLL3=reshape(LL3,1,[]); 
SL3=std(LLL3);  
%比较标准差最大 
SL=max(max(SL1,SL2),SL3);   
G = fspecial('gaussian', [5 5], 1); 
GL1=imfilter(LL1, G, 'circular'); 
hist=imhist(GL1)/prod(size(GL1)); 
G1=find(hist); 
H1=-hist(G1)'*log2(hist(G1));  
GL2=imfilter(LL2, G, 'circular'); 
hist=imhist(GL2)/prod(size(GL2)); 
G2=find(hist); 
H2=-hist(G2)'*log2(hist(G2));  
GL3=imfilter(LL3, G, 'circular'); 
hist=imhist(GL3)/prod(size(GL3)); 
G3=find(hist); 
H3=-hist(G3)'*log2(hist(G3));  
%比较二维熵最小的 
H=min(min(H1,H2),H3);  
if(SL==SL1)      
    ZL=LL1; 
end 
if(SL==SL2)      
    ZL=LL2; 
end 
if(SL==SL3)      
    ZL=LL3; 
end  
if(H==H1)     
    HL=LL1; 
end 
if(H==H2)     
    HL=LL2; 
end 
if(H==H3)      
    HL=LL3;   
end      
%计算初始显著图 
C=0.35*ZL+0.65*HL;   
[Z E]=lrr(C,0.01);%全局低秩Z为低秩部分E为稀疏部分   
ZZ=(C-Z).*C;   
figure,imshow(ZZ,[]);

这样就可以保持输出图片与原图像的大小一致。