retinex相关代码汇总
混合方法 SSR.m
matlab代码,本来是RGB,改成了处理灰度图像的。
%%%%%%%%%%%%%%%RGB normalisation%%%%%%%%%%%%%%%%%%%%%% %its cascaded implementain of 1 section of paper "A FAST SKIN REGION DETECTOR" by %Phil Chen, Dr.Christos Greecos %and %section 2.1 of paper "Simple and accurate face detection in color images" by %YUI TING PAI et al % Coding by Madhava.S.Bhat, Dept of Electronics an communication %Dr.Ambedkar Institute of Technology, Bangalore %madhava.s@dr-ait.org function[]= SSR(IMG) IMG=rgb2gray(IMG); figure,imshow(IMG) title('original') R=double(IMG); [H,W]=size(R); % minR=0; % minG=0; % minB=0; % [srow,scol]=find(R==0 & G==0 & B==0); % if(isempty(srow) && isempty(scol)) minR=min(min(R)); % end R=R-minR; S=zeros(H,W); [srow,scol]=find(R==0); [sm,sn]=size(srow); for i=1:sm S(srow(i),scol(i))=1; end mstd=sum(sum(S)) Nstd=(H*W)-mstd; Cst=0; Cst=double(Cst); for i=1:H for j=1:W a=R(i,j); b=R(i,j); Cst=a+b+Cst; end end %%%%sum of black pixels%%%%%%%%%%% blacksumR=0; for i=1:sm blacksumR=blacksumR+R(srow(i),scol(i)); end Cstd = Cst/(2*Nstd) CavgR=sum(sum(R))./(H*W) Rsc=Cstd./CavgR R=R.*Rsc; C=R; C=C/255; Y=C; figure,imshow(C) title('aft 1st stage of compensation') %normalize Y minY=min(min(Y)); maxY=max(max(Y)); Y=255.0*(Y-minY)./(maxY-minY); YEye=Y; Yavg=sum(sum(Y))/(W*H) T=1; if (Yavg<64) T=1.4 elseif (Yavg>192) T=0.6 end T if (T~=1) RI=R.^T; else RI=R; end Cfinal=uint8(RI); figure,imshow(Cfinal) title('Light intensity compensated')
clc; clear all; %%%%%%sourceImage%%%%%%%%% sourceImage = imread('F:\Users\*****\Desktop\**图像\test.bmp'); %imshow(sourceImage); SSR(sourceImage);
效果不对,不知道哪有问题:
看灰度图的处理效果还可以。
【转载自】
图像增强算法四种,图示与源码,包括retinex(ssr、msr、msrcr)和一种混合算法 - onezeros的专栏 - CSDN博客 https://blog.csdn.net/onezeros/article/details/6342661
【其他】
SSR matlab实现单尺度retinex算法,实现图像增强。 联合开发网 - pudn.com http://www.pudn.com/Download/item/id/2776026.html
%retinex% clc; clear all; %%%%%%sourceImage%%%%%%%%% sourceImage = imread('C:\Users\huang\Desktop\����1.bmp'); imshow(sourceImage); %%%R,G,B%%%% image_r=sourceImage(:,:,1); image_g=sourceImage(:,:,2); image_b=sourceImage(:,:,3); %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% r=100; cParam=200; block=2*r+1; sum=0.0; for i=1:block for j=1:block gauss(i,j)=exp((-((i-r-1)^2+(j-r-1)^2))/cParam^2); sum=sum+gauss(i,j); end end for i=1:block for j=1:block gauss(i,j)=gauss(i,j)/sum; end end %%%%%%%%%%%R%%%%%%%%%%%%% Img = double(image_r); K=imfilter(Img,gauss,'replicate','conv'); G=log(Img+1)-log(K+1); mi=min(min(G)); ma=max(max(G)); destImage_r=(G-mi)*255/(ma-mi); %%%%%%%%%%%%%%G%%%%%%%%%%%%% Img = double(image_g); K=imfilter(Img,gauss,'replicate','conv'); G=log(Img+1)-log(K+1); mi=min(min(G)); ma=max(max(G)); destImage_g=(G-mi)*255/(ma-mi); %%%%%%%%%%%%%B%%%%%%%%%%%%%%%%%% Img = double(image_b); K=imfilter(Img,gauss,'replicate','conv'); G=log(Img+1)-log(K+1); mi=min(min(G)); ma=max(max(G)); destImage_b=(G-mi)*255/(ma-mi); %%%%%%%%%%%%%%%%%% destImageSSR=cat(3,destImage_r,destImage_g,destImage_b); figure; imshow(uint8(destImageSSR)); %etinex clc %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% r=100; cParam1=30; cParam2=100; cParam3=300; block=2*r+1; sum1=0.0; sum2=0.0; sum3=0.0; for i=1:block for j=1:block gauss1(i,j)=exp((-((i-r-1)^2+(j-r-1)^2))/cParam1^2); sum1=sum1+gauss1(i,j); gauss2(i,j)=exp((-((i-r-1)^2+(j-r-1)^2))/cParam2^2); sum2=sum2+gauss2(i,j); gauss3(i,j)=exp((-((i-r-1)^2+(j-r-1)^2))/cParam3^2); sum3=sum3+gauss3(i,j); end end for i=1:block for j=1:block gauss1(i,j)=gauss1(i,j)/sum1; gauss2(i,j)=gauss2(i,j)/sum2; gauss3(i,j)=gauss3(i,j)/sum3; end end %%%%%%%%%%%R%%%%%%%%%%%%% Img = double(image_r); K1=imfilter(Img,gauss1,'replicate','conv'); K2=imfilter(Img,gauss2,'replicate','conv'); K3=imfilter(Img,gauss3,'replicate','conv'); G=log(Img+1)-(1/3)*(log(K1+1)+log(K2+1)+log(K3+1)); mi=min(min(G)); ma=max(max(G)); destImage_r=(G-mi)*255/(ma-mi); %%%%%%%%%%%%%%G%%%%%%%%%%%%% Img = double(image_g); K1=imfilter(Img,gauss1,'replicate','conv'); K2=imfilter(Img,gauss2,'replicate','conv'); K3=imfilter(Img,gauss3,'replicate','conv'); G=log(Img+1)-(1/3)*(log(K1+1)+log(K2+1)+log(K3+1)); mi=min(min(G)); ma=max(max(G)); destImage_g=(G-mi)*255/(ma-mi); %%%%%%%%%%%%%B%%%%%%%%%%%%%%%%%% Img = double(image_b); K1=imfilter(Img,gauss1,'replicate','conv'); K2=imfilter(Img,gauss2,'replicate','conv'); K3=imfilter(Img,gauss3,'replicate','conv'); G=log(Img+1)-(1/3)*(log(K1+1)+log(K2+1)+log(K3+1)); mi=min(min(G)); ma=max(max(G)); destImage_b=(G-mi)*255/(ma-mi); %%%%%%%%%%%%%%%%%% destImageMSR=cat(3,destImage_r,destImage_g,destImage_b); figure; imshow(uint8(destImageMSR));
View Code
【别人博客里的一些效果图】
retinex图像增强算法的研究 - zmshy2128 - 博客园 https://www.cnblogs.com/zmshy2128/p/6126987.html
关于Retinex图像增强算法的一些新学习。 - Imageshop - 博客园 https://www.cnblogs.com/Imageshop/p/3810402.html
Retinex图像增强算法代码 - liyingjiang22的博客 - CSDN博客 https://blog.csdn.net/liyingjiang22/article/details/52903127
图像增强处理之:同态滤波与Retinex算法(二)McCann Retinex和McCann99 Retinex迭代算法 - 满城风絮 - CSDN博客 https://blog.csdn.net/piaoxuezhong/article/details/78248219
转载于:https://www.cnblogs.com/wxl845235800/p/10397426.html
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