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 = displayDictionaryElementsAsImage2(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) = 1; %min(min(D));
- I(:,:,2) = 1; %min(min(D));
- I(:,:,3) = 1; %max(max(D));
- % %%% 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
