【图像去雾】基于matlab暗通道先验图像去雾【含Matlab源码 3547期】.zip

function R = anyuanse(m_img) % 原始图像 I=double(m_img)/255; % 获取图像大小 [h,w,c]=size(I); win_size = 7; img_size=w*h; dehaze=zeros(img_size*c,1); dehaze=reshape(dehaze,h,w,c); win_dark=zeros(img_size ,1); for cc=1:img_size win_dark(cc)=1; end %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%5 win_dark=reshape(win_dark,h,w); %计算分块深度darkchannel for j=1+win_size:w-win_size for i=win_size+1:h-win_size m_pos_min = min(I(i,j,:)); for n=j-win_size:j+win_size for m=i-win_size:i+win_size if(win_dark(m,n)>m_pos_min) win_dark(m,n)=m_pos_min; end end end end end %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%5 %图像透射率预处理，深度图反相 for cc=1:img_size win_dark(cc)=1-win_dark(cc); end %%%%%%%%%%%%%%%%%图像软抠图开始%%%%%%%%%%%%%%%%%%%%% %选定精确dark value坐标 win_b = zeros(img_size,1); for ci=1:h for cj=1:w if(rem(ci-8,15)<1) %没有余数？ if(rem(cj-8,15)<1) win_b(ci*w+cj)=win_dark(ci*w+cj); end end end end %显示分块darkchannel neb_size = 9; win_size = 1; epsilon = 0.0000001; %指定矩阵形状 indsM=reshape([1:img_size],h,w); %计算矩阵L tlen = img_size*neb_size^2; row_inds=zeros(tlen ,1); col_inds=zeros(tlen,1); vals=zeros(tlen,1); len=0; for j=1+win_size:w-win_size for i=win_size+1:h-win_size if(rem(ci-8,15)<1) if(rem(cj-8,15)<1) continue; end end win_inds=indsM(i-win_size:i+win_size,j-win_size:j+win_size); win_inds=win_inds(:);%列显示 winI=I(i-win_size:i+win_size,j-win_size:j+win_size,:); winI=reshape(winI,neb_size,c); %三个通道被拉平成为一个二维矩阵 3*9 win_mu=mean(winI,1)'; %求每一列的均值 如果第二个参数为2 则为求每一行的均值 //矩阵变向量 win_var=inv(winI'*winI/neb_size-win_mu*win_mu' +epsilon/neb_size*eye(c)); %求方差 winI=winI-repmat(win_mu',neb_size,1);%求离差 tvals=(1+winI*win_var*winI')/neb_size;% 求论文所指的矩阵L row_inds(1+len:neb_size^2+len)=reshape(repmat(win_inds,1,neb_size),neb_size^2,1); col_inds(1+len:neb_size^2+len)=reshape(repmat(win_inds',neb_size,1),neb_size^2,1); vals(1+len:neb_size^2+len)=tvals(:); len=len+neb_size^2; end end vals=vals(1:len); row_inds=row_inds(1:len); col_inds=col_inds(1:len); %创建稀疏矩阵 A=sparse(row_inds,col_inds,vals,img_size,img_size); %求行的总和 sumA为列向量 sumA=sum(A,2); %spdiags(sumA(:),0,img_size,img_size) 创建img_size大小的稀疏矩阵其元素是sumA中的列元素放在由0指定的对角线位置上。 A=spdiags(sumA(:),0,img_size,img_size)-A; %创建稀疏矩阵 D=spdiags(win_b(:),0,img_size,img_size); lambda=1; x=(A+lambda*D)\(lambda*win_b(:).*win_b(:)); %%%%%%%%%%%%%%%%%%%%%%%%%软图像抠图结束%%%%%%%%%%%%%%%55 %去掉0-1范围以外的数 alpha=max(min(reshape(x,h,w),1),0);%图像透射率 A=220/255; %大气光没有去计算(直接定义为220，一般也在改值附近) %去雾 for i=1:c for j=1:h for l=1:w dehaze(j,l,i)=(I(j,l,i)-A)/alpha(j,l)+A; end end end R = dehaze;