稀疏表示字典的显示（MATLAB实现代码）

[置顶] 稀疏表示字典的显示（MATLAB实现代码）

2016-01-05 19:34  400人阅读  评论(0)  收藏  举报

  分类：

 

ImageSuperResolution（10）    Compressive Sensing（6）    Machine Learning（21） 

版权声明：本文为博主原创文章，未经博主允许不得转载。

本文主要是实现论文--基于稀疏表示的图像超分辨率《Image Super-Resolution Via Sparse Representation》中的Figure2，通过对100000个高分辨率和低分辨率图像块训练得到的高分辨率图像块字典，字典原子总数为512，图像块尺寸大小为9X9

方法一：

 clc;
 clear all;

 % load dictionary
 load('Dictionary/D_512_0.15_9.mat');

 patch_size=9;
 nRow=24;
 nCol=22;
 D=Dh';
 w=nCol*patch_size;
 h=nRow*patch_size;

 gridx = 1:patch_size :w;
 gridx = [gridx, w-patch_size+1];
 gridy = 1:patch_size : h;
 gridy = [gridy, h-patch_size+1];
 K=512; %字典原子总数
 DD=cell(1,K);
 row=length(gridx);
 col=length(gridy);
 hIm=zeros([w,h]);
 for i=1:K
     DD{i}=D(i,:);
 end

 for ii = 1:length(gridx),
     for jj = 1:length(gridy),
         yy = gridx(ii);
         xx = gridy(jj);
         if (ii-1)*nRow+jj >K
             break
         end
         temp=DD{(ii-1)*nCol+jj};
         hPatch=reshape(temp,[patch_size,patch_size]);
         hIm(yy:yy+patch_size-1, xx:xx+patch_size-1) = hIm(yy:yy+patch_size-1, xx:xx+patch_size-1) +hPatch;
      end
 end

 figure;
 imagesc(hIm);
 colormap(gray);
 axis image;

输出结果：

可以看出，相比于论文中字典的显示图，颜色有点浅，通过调节MATLAB的colorbar，可以将背景颜色变深，

结果如下图所示：

方法二：

通过http://www.cs.technion.ac.il/~elad/software/提供的ksvd工具箱中的displayDictionaryElementsAsImage( )函数，来实现字典的显示。

displayDictionaryElementsAsImage.m

 function I = displayDictionaryElementsAsImage(D, numRows, numCols,X,Y,sortVarFlag)
 % function I = displayDictionaryElementsAsImage(D, numRows, numCols, X,Y)
 % displays the dictionary atoms as blocks. For activation, the dictionary D
 % should be given, as also the number of rows (numRows) and columns
 % (numCols) for the atoms to be displayed. X and Y are the dimensions of
 % each atom.

 borderSize = 1;
 columnScanFlag = 1;
 strechEachVecFlag = 1;
 showImFlag = 1;

 if (length(who('X'))==0)
     X = 8;
     Y = 8;
 end
 if (length(who('sortVarFlag'))==0)
     sortVarFlag = 1;
 end

 numElems = size(D,2);
 if (length(who('numRows'))==0)
     numRows = floor(sqrt(numElems));
     numCols = numRows;
 end
 if (length(who('strechEachVecFlag'))==0)
     strechEachVecFlag = 0;
 end
 if (length(who('showImFlag'))==0)
     showImFlag = 1;
 end

 %%% sort the elements, if necessary.
 %%% construct the image to display (I)
 sizeForEachImage = sqrt(size(D,1))+borderSize;
 I = zeros(sizeForEachImage*numRows+borderSize,sizeForEachImage*numCols+borderSize,3);
 %%% fill all this image in blue
 I(:,:,1) = 0; %min(min(D));
 I(:,:,2) = 0; %min(min(D));
 I(:,:,3) = 1; %max(max(D));

 %%% now fill the image squares with the elements (in row scan or column
 %%% scan).
 if (strechEachVecFlag)
     for counter = 1:size(D,2)
         D(:,counter) = D(:,counter)-min(D(:,counter));
         if (max(D(:,counter)))
             D(:,counter) = D(:,counter)./max(D(:,counter));
         end
     end
 end


 if (sortVarFlag)
     vars = var(D);
     [V,indices] = sort(vars');
     indices = fliplr(indices);
     D = [D(:,1:sortVarFlag-1),D(:,indices+sortVarFlag-1)];
     signs = sign(D(1,:));
     signs(find(signs==0)) = 1;
     D = D.*repmat(signs,size(D,1),1);
     D = D(:,1:numRows*numCols);
 end

 counter=1;
 for j = 1:numRows
     for i = 1:numCols
 %         if (strechEachVecFlag)
 %             D(:,counter) = D(:,counter)-min(D(:,counter));
 %             D(:,counter) = D(:,counter)./max(D(:,counter));
 %         end
 %         if (columnScanFlag==1)
 %             I(borderSize+(i-1)*sizeForEachImage+1:i*sizeForEachImage,borderSize+(j-1)*sizeForEachImage+1:j*sizeForEachImage,1)=reshape(D(:,counter),8,8);
 %             I(borderSize+(i-1)*sizeForEachImage+1:i*sizeForEachImage,borderSize+(j-1)*sizeForEachImage+1:j*sizeForEachImage,2)=reshape(D(:,counter),8,8);
 %             I(borderSize+(i-1)*sizeForEachImage+1:i*sizeForEachImage,borderSize+(j-1)*sizeForEachImage+1:j*sizeForEachImage,3)=reshape(D(:,counter),8,8);
 %         else
             % Go in Column Scan:
             I(borderSize+(j-1)*sizeForEachImage+1:j*sizeForEachImage,borderSize+(i-1)*sizeForEachImage+1:i*sizeForEachImage,1)=reshape(D(:,counter),X,Y);
             I(borderSize+(j-1)*sizeForEachImage+1:j*sizeForEachImage,borderSize+(i-1)*sizeForEachImage+1:i*sizeForEachImage,2)=reshape(D(:,counter),X,Y);
             I(borderSize+(j-1)*sizeForEachImage+1:j*sizeForEachImage,borderSize+(i-1)*sizeForEachImage+1:i*sizeForEachImage,3)=reshape(D(:,counter),X,Y);
 %         end
         counter = counter+1;
     end
 end

 if (showImFlag)
     I = I-min(min(min(I)));
     I = I./max(max(max(I)));
     imshow(I,[]);
 end

测试程序

displayDictionary_test.m

 clc;
 clear all;

 %加载字典
 load('F:\Research\ScSR\ScSR\Dictionary\D_512_0.15_9.mat');

 patch_size=9;
 D=Dh;
 K=512;
 figure;
 %调用KSVD工具箱中的字典显示函数
 im=displayDictionaryElementsAsImage(D, floor(sqrt(K)), floor(size(D,2)/floor(sqrt(K))),patch_size,patch_size);

输出结果：

方法三：

因为方法一显示的字典图像偏灰，对比度不强，所以通过对字典原子像素值进行拉伸变化到0-1，增强图像对比度。

 clc;
 clear all;

 % load dictionary
 load('Dictionary/D_512_0.15_9.mat');

 patch_size=9;
 nRow=24;
 nCol=22;
 D=Dh';
 w=nCol*patch_size;
 h=nRow*patch_size;

 gridx = 1:patch_size :w;
 gridx = [gridx, w-patch_size+1];
 gridy = 1:patch_size : h;
 gridy = [gridy, h-patch_size+1];
 K=512; %字典原子总数
 DD=cell(1,K);
 row=length(gridx);
 col=length(gridy);
 hIm=zeros([w,h]);
 for i=1:K
     DD{i}=D(i,:);
 end

 for ii = 1:length(gridx),
     for jj = 1:length(gridy),
         yy = gridx(ii);
         xx = gridy(jj);
         if (ii-1)*nRow+jj >K
             break
         end
         temp=DD{(ii-1)*nCol+jj};
         hPatch=reshape(temp,[patch_size,patch_size]);
         I=hPatch;
         I = I-min(min(min(I)));
         I = I./max(max(max(I)));%对字典原子像素值进行拉伸变化到0-1
         hIm(yy:yy+patch_size-1, xx:xx+patch_size-1) = hIm(yy:yy+patch_size-1, xx:xx+patch_size-1) +I;
      end
 end

 figure;
 imshow(hIm);

调整参数，将字典原子像素值拉伸变换到0-0.7

 hPatch=reshape(temp,[patch_size,patch_size]);
 I=hPatch;
 I = I-min(min(min(I)));
 I = 0.7*I./max(max(max(I)));%对字典原子像素值进行拉伸变化到0-0.7

顶

4

踩