【代码备份】pocs.m

超分辨率算法代码

POCS算法，凸集投影法。

pocs.m，没有调用的代码，没看懂。。只有这个函数。。抱歉。

function y = pocs(s,delta_est,factor)
% POCS - reconstruct high resolution image using Projection On Convex Sets
%    y = pocs(s,delta_est,factor)
%    reconstruct an image with FACTOR times more pixels in both dimensions
%    using Papoulis Gerchberg algorithm and using the shift and rotation 
%    information from DELTA_EST and PHI_EST
%    in:
%    s: images in cell array (s{1}, s{2},...)
%    delta_est(i,Dy:Dx) estimated shifts in y and x
%    factor: gives size of reconstructed image

%% -----------------------------------------------------------------------
% SUPERRESOLUTION - Graphical User Interface for Super-Resolution Imaging
% Copyright (C) 2005-2007 Laboratory of Audiovisual Communications (LCAV), 
% Ecole Polytechnique Federale de Lausanne (EPFL), 
% CH-1015 Lausanne, Switzerland 
% 
% This program is free software; you can redistribute it and/or modify it 
% under the terms of the GNU General Public License as published by the 
% Free Software Foundation; either version 2 of the License, or (at your 
% option) any later version. This software is distributed in the hope that 
% it will be useful, but without any warranty; without even the implied 
% warranty of merchantability or fitness for a particular purpose. 
% See the GNU General Public License for more details 
% (enclosed in the file GPL). 
%
% Latest modifications: August 20, 2006, by Karim Krichane

max_iter = 50;

temp = upsample(upsample(s{1}, factor)', factor)';
y = zeros(size(temp));
coord = find(temp);
y(coord) = temp(coord);


for i = 2:length(s)
    temp = upsample(upsample(s{i}, factor)', factor)';
    temp = shift(temp, round(delta_est(i, 2)*factor), round(delta_est(i, 1)*factor));
    coord = find(temp);
    y(coord) = temp(coord);
end
   
y_prev=y;

E=[];
iter=1;

blur =[.25 0 1 0 .25;...
        0  1 2 1  0;...
        1  2 4 2  1;...
        0  1 2 1  0;...
       .25 0 1 0 .25];
   
blur = blur / sum(blur(:));
wait_handle = waitbar(0, '重构中...', 'Name', '超分辨率重构');

while iter < max_iter
   waitbar(min(4*iter/max_iter, 1), wait_handle);
   y = imfilter(y, blur);   
   for i = length(s):-1:1
        temp = upsample(upsample(s{i}, factor)', factor)';
        temp = shift(temp, round(delta_est(i, 2)*factor), round(delta_est(i, 1)*factor));
        coord = find(temp);
        y(coord) = temp(coord);
   end
   
   delta= norm(y-y_prev)/norm(y);
   E=[E; iter delta];
   iter = iter+1;
   if iter>3 
     if abs(E(iter-3,2)-delta) <1e-4
        break  
     end
   end
   y_prev=y;
%    if mod(iter,10)==2
%        disp(['iteration ' int2str(E(iter-1,1)) ', error ' num2str(E(iter-1,2))])
%    end
end

close(wait_handle);

 

【其他】貌似这个里面有，可以试一下，没下载过

凸集投影法（POCS）超分辨重建算法MATLAB实现 https://download.csdn.net/download/styyzxjq2009/2312854

POCS 提供了基于POCS算法的超分辨率图像重建的源程序 联合开发网 - pudn.com http://www.pudn.com/Download/item/id/3028355.html

超分辨率的POCS算法–MATLAB中文论坛 http://www.ilovematlab.cn/thread-135641-1-1.html

---

POCS.m:

close all 
clear 
clc 
t1=clock; 
NumberOfFrames =3;  
k = zeros(1,4);  
%%% 第一帧低分辨率图像与原图 
RefImage = imread('a_0.jpg');        %第一帧LW图像 
origin=imread('origin.jpg');    %原图 
figure(1);  
imshow(RefImage) 
RefImageImage =double(RefImage); 
%%%差值处理，spline，nearest，linear，cubic 
[x, y] = meshgrid(1:size(RefImage,2), 1:size(RefImage,1));  
[X, Y] = meshgrid(1:2.*size(RefImage,2), 1:2.*size(RefImage,1));  
upRefImage = interp2(x,y,double(RefImage),X./2,Y./2,'spline');  
upRefImage(isnan(upRefImage)) = 0;  
upRefImage=wiener2(upRefImage); 
figure(2);  
imshow(mat2gray(upRefImage)) 
imwrite(mat2gray(upRefImage),'RefImage_filter_nearest.jpg') 
%计算信噪比PSNR 
c=zeros(); 
[m,n]=size(origin) 
for i=1:1:m 
    for j=1:1:n 
        minus(i,j)=(origin(i,j)-upRefImage(i,j))^2; 
    end 
end 
summ=sum(sum(minus));        
PSNR=10*log10(255^2*m*n/summ) 
%迭代次数 
for iter=1:8,  
  disp(iter);  
  for num = 2:NumberOfFrames,  
 
    %读入其他帧数图像 
    if (num < 8);  
      frame = imread(strcat('C:\Users\chen\Desktop\POCS\code\a_',num2str(num),'.jpg'));  
    else  
      frame = imread(strcat('C:\Users\chen\Desktop\POCS\code\a_',num2str(num),'.jpg'));  
    end  
    frame = double(frame); 
 
    %%%计算相对第一帧的位置 
    k = affine(frame,RefImage);  
    u =  k(1).*X + k(2).*Y + 2.*k(3);  
    v = -k(2).*X + k(1).*Y + 2.*k(4);  
    mcX = X + u;  
    mcY = Y + v;  
    for m2 = 1:size(frame,2),  
      for m1 = 1:size(frame,1),  
        n1 = 2*m1;  
        n2 = 2*m2;  
        N2 = mcX(n1,n2);  
        N1 = mcY(n1,n2);  
        if ( N1>3 & N1<size(upRefImage,1)-2 & N2>3 & N2<size(upRefImage,2)-2 )  
        rN1 = round(N1);  
        rN2 = round(N2);  
        windowX = Y(rN1-2:rN1+2,rN2-2:rN2+2);  
        windowY = X(rN1-2:rN1+2,rN2-2:rN2+2);  
        weights = exp(-((N1-windowX).^2+(N2-windowY).^2)./2);  
        weights = weights./sum(sum(weights));  
        Ihat = sum(sum(weights.*upRefImage(rN1-2:rN1+2,rN2-2:rN2+2)));  
        R = frame(m1,m2) - Ihat;  
 
        temp = 0;  
 
    %%% 计算新值 
        if (R>1)  
          convertedR=double(R); 
          upRefImage(rN1-2:rN1+2,rN2-2:rN2+2) = upRefImage(rN1-2:rN1+2,rN2-2:rN2+2) + ...  
              (weights.*(convertedR-1))./sum(sum(weights.^2));  
        elseif (R<-1)  
          convertedR=double(R); 
          upRefImage(rN1-2:rN1+2,rN2-2:rN2+2) = upRefImage(rN1-2:rN1+2,rN2-2:rN2+2) + ...  
              (weights.*(convertedR+1))./sum(sum(weights.^2));  
        end  
      end  
    end  
  end  
 
  upRefImage(upRefImage<0) = 0;  
  upRefImage(upRefImage>255) = 255;  
 
end  
end  
%%%展示图像 %%%  
 imwrite(mat2gray(upRefImage),'SRframe_cubic.jpg');  
t2=clock; 
disp(['程序总运行时间：',num2str(etime(t2,t1))]); 
figure(3);  
imshow(mat2gray(upRefImage)) 

 

另一种POCS算法，myPOCScode.m:

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 
% POCS Image Reconstruction 
% ------------------------- 
%  AUTHOR: Stephen Rose, Maher Khoury 
%    DATE: March 1, 1999 
% PURPOSE: Generates SR frame using the POCS method 
% 
% Notes: 
%   -init.m contains the affine transformation parameters ？？？？？？？
%   -Assuming a gaussian PSF 
%   -u,v are affine transformation vectors for (x,y) 
%   -mcX,mcY are transformed coordines in SR frame 
% 
% Variables: 
%   -ref            = LR reference frame 
%   -upref          = HR reference frame 
%   -NumberOfFrames = Number of pixel frames to consider 
%   -frame          = LR frame currently being examined 
%   -weights        = weights based on Gaussian PSF 
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% 
%%% Initialization 初始化？？？？
%init; 
clear;
close all
clc
% NumberOfFrames = 4; 
k = zeros(1,4); 
wd=1;
dlt=5;
% max_iter=1;
q=2;%放大倍数

% I=imread('E:\SR\mmread\disk\frame1.bmp');
% [m n]=size(I);
% up_ref=zeros(q.*m,q.*n,17);
%逐次选择初始图像

    
%%% Create the high-resolution reference frame 
% ref=imread(E:\SR\mmread\disk\frame1.bmp');%低分辨率参考帧
ref=imread('frame1.bmp');
ref=ref(:,:,1);
% ref = ref(1:size(ref,1)./2,1:size(ref,2)./2);
ref=double(ref);
%ref = ref(1:2:size(ref,1),1:2:size(ref,2)); 
% figure,imshow(ref,[]);
%  imwrite(mat2gray(ref),'ref.bmp');  
% I0=imread('cameraman.bmp');%读入原始清晰图像（计算mse、psnr时，需要用）
% mse=zeros(1,max_iter);
% psnr=zeros(1,max_iter);
% up_ref=zeros(q.*size(ref,1),q.*size(ref,2),iter_max);
% for iter_max=1:max_iter
%     disp(strcat('最大迭代次数:',num2str(iter_max))); 
% for dlt=1:6
%%%Interpolate values at inbetween points 插值过程
[x, y] = meshgrid(1:size(ref,2), 1:size(ref,1)); 
[X, Y] = meshgrid(1:q.*size(ref,2), 1:q.*size(ref,1)); 
upref = interp2(x,y,ref,X./q,Y./q,'bicubic'); %或者linear,bicubic
upref1=upref;
upref1(isnan(upref1)) = 0; 
[m,n]=size(upref);

% figure,imshow(upref,[]); 
% imwrite(mat2gray(upref),'upref0.bmp');
% drawnow; 

%%% Iterate the entire process 迭代过程
% for iter=1:iter_max
%     disp(strcat('第',num2str(iter),'次迭代')); 
  %%% Iterate over the frames 逐帧迭代
  for num = 2:4   
      frame = imread(strcat('frame',num2str(num),'.bmp')); 
      frame=frame(:,:,1);
      frame=double(frame);
       
%        frame = frame(1:size(frame,1)./q,1:size(frame,2)./q); 


    %%%Calculate the affine motion parameters for this frame 
    %%%计算该帧的仿射系数（估计图像配准参数）
    k = affine(frame,ref);
    u =  k(1).*X + k(2).*Y + q.*k(3); 
    v = -k(2).*X + k(1).*Y + q.*k(4); 

    %%% Calculate the coordinates of the motion compensated pixels
    %%% %计算运动补偿像素的坐标？？？？？
    mcX = X + u; 
    mcY = Y + v; 
%     Imin=min(min(frame));
%     Imax=max(max(frame));
%     Rel=zeros(m,n);
%     for k=1:m
%         for j=1:n
%             Rel(k,j)=0.1*(1-2/(Imax-Imin)*abs(upref(k,j)-(Imax-Imin)/2));
%         end
%     end
    %%% Loop over entire (low-res) frame 逐像素修正
    for m2 = 1:size(frame,2) 
      for m1 = 1:size(frame,1)
         
        %%% Get high-resolution coordinates 
        n1 = 2*m1; 
        n2 = 2*m2; 

        %%% Get coordinates of the motion compensated pixel 获取运动补偿像素的坐标
        N2 = mcX(n1,n2); 
        N1 = mcY(n1,n2); 

        %%% If not a border pixel 排除边缘像素
        if ( N1>=wd+1 & N1<=size(upref,1)-wd & N2>=wd+1 & N2<=size(upref,2)-wd ) %？？？？？？原程序为：N1>wd+1 & N1<size(upref,1)-wd

        %%% Find center of the window where the PSF will be applied
        %%% 获取PSF作用范围的中心点
        rN1 = round(N1); 
        rN2 = round(N2); 

        %%% Calculate the effective window 计算窗口作用范围
        windowX = Y(rN1-wd:rN1+wd,rN2-wd:rN2+wd); 
        windowY = X(rN1-wd:rN1+wd,rN2-wd:rN2+wd); 

        %%% Find the value of the gaussian at these points and normalize
        %%% 计算PSF并归一化
%         weights = exp(-1/wd^2*((N1-windowX).^2+(N2-windowY).^2)./2); 
        %%原代码如下计算weights
        weights = exp(-((N1-windowX).^2+(N2-windowY).^2)./2); 
        weights = weights./sum(sum(weights)); 

        %%% Calculate the value of the estimate Ihat 计算投影像素的估计值
        Ihat = sum(sum(weights.*upref(rN1-wd:rN1+wd,rN2-wd:rN2+wd)));

        %%% Calculate the residual 计算残差
        R(m1,m2) = frame(m1,m2) - Ihat;

        temp = 0; 

        %%% Calculate new values for the reference frame 修正该点的像素值
        if (R(m1,m2)>dlt) 
          upref(rN1-wd:rN1+wd,rN2-wd:rN2+wd) = upref(rN1-wd:rN1+wd,rN2-wd:rN2+wd) + (weights.*(R(m1,m2)-dlt))./sum(sum(weights.^2)); 
%           upref(rN1-wd:rN1+wd,rN2-wd:rN2+wd) = upref(rN1-wd:rN1+wd,rN2-wd:rN2+wd) +Rel(rN1-wd:rN1+wd,rN2-wd:rN2+wd).*(R(m1,m2)-dlt);
        elseif (R(m1,m2)<-dlt) 
          upref(rN1-wd:rN1+wd,rN2-wd:rN2+wd) = upref(rN1-wd:rN1+wd,rN2-wd:rN2+wd) + (weights.*((R(m1,m2)+dlt))./sum(sum(weights.^2)));
%           upref(rN1-wd:rN1+wd,rN2-wd:rN2+wd) = upref(rN1-wd:rN1+wd,rN2-wd:rN2+wd) +Rel(rN1-wd:rN1+wd,rN2-wd:rN2+wd).*(R(m1,m2)-dlt);
%          else
%                 upref(rN1-wd:rN1+wd,rN2-wd:rN2+wd) = upref(rN1-wd:rN1+wd,rN2-wd:rN2+wd) + Rel(rN1-wd:rN1+wd,rN2-wd:rN2+wd).*R(m1,m2); 
        end 
        end 
    end 
  end 

  upref(upref<0) = 0; 
  upref(upref>255) = 255; 

end 

%upref=255/max(max(upref))*upref;
%%% Display the image %%% 
% up_ref(:,:,start)=uint8(upref);

% imwrite(mat2gray(upref),strcat('upref',num2str(start),'.bmp'));

% % % %  计算mse与psnr
% mse(1,iter_max)=MSE(I0,up_ref(:,:,iter_max));
% psnr(1,iter_max)=PSNR(I0,up_ref(:,:,iter_max));

% imwrite(upref,'SRgirl.tif'); 
figure,imshow(upref,[]); 
figure,imshow(upref1,[]);
% imwrite(mat2gray(upref),'upref.bmp');
% g=midfilter(upref,1);
% figure,imshow(g)
% gg=imread('jichang.bmp');
% figure,imshow(gg);
% drawnow; 

% for i=1:10
%     up_ref(:,:,i)=double(up_ref(:,:,i));
%     imwrite(mat2gray(up_ref(:,:,i),strcat('up_ref',num2str(i),'.bmp')));
% end
    
  

 

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