implementation for iterative wiener filter

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gehad attia 2012-8-1

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链接

此问题的直接链接

https://ww2.mathworks.cn/matlabcentral/answers/45015-implementation-for-iterative-wiener-filter

This is my implementation in the iterative wiener filter in this paper : http://www.tsc.uc3m.es/~navia/LATDS07/IterativeWienerFilter.pdf

I wish it will help anyone

function wiener()
clc;
clear;
f=im2double(rgb2gray(imread('lena.jpg')));
imshow(f);
f=imresize(f,[32 32]);
figure,imshow(f)
[r c]=size(f);
h=fspecial('average');
g=imfilter(f,h,'circular');
s_avg = sum(sum(f))/(r*c);
SNR=90;
n_sigma=s_avg/(10^(SNR/20));
n=n_sigma*randn(size(f));
g=g+n;
[Nf,Mf]=size(g);
[Nh,Mh]=size(h);
L1=floor(Nh/2);
L2=floor(Mh/2);
H=zeros(Nf*Mf);
k=1;
for row=1:Mf,
      for col=1:Nf,
          hh=zeros(Nf,Mf);
          hh(1:Nh,1:Mh)=h;
          hh=circshift(hh,[col-1-L1,row-1-L2]);
          H(k,:)=hh(:)';
          k=k+1;
      end
  end
%%make vector of m^2*1 of the f,n,g
f=reshape(f',size(f,1)*size(f,2),1);
g=reshape(g',size(g,1)*size(g,2),1);
n=reshape(n',size(n,1)*size(n,2),1);
%%%calculate the autocorrelation matrix of f ,g,n
u=mean(g);
g1=autom(g-u);
Rg=toeplitz(g1);
n1=autom(n);
Rn=toeplitz(n1);%%%%%
Rf=Rg;
steps=10;
mse=zeros(1,steps);
for i=1:steps
      B=Rf*H'*inv( (H*Rf*H') +Rn);
      fHat=B*(g); 
      Rf=B*Rg*B';
      im=reshape(fHat,[32 32]);
      g=reshape(g,[32 32]);
      %figure,imshow(im',[]);
      mse(1,i) = sum(sum((im(:)-g(:))));
      g=reshape(g',size(g,1)*size(g,2),1);
end
t=1:steps;
mse
plot(t,mse);
end
function [Rxx]=autom(x)
N=length(x);
Rxx=zeros(1,N);
for m=1: N+1
      for n=1: N-m+1
          Rxx(m)=(Rxx(m)+x(n)*x(n+m-1))/N-m+1;
      end;
end
end