资源简介
K-SVD稀疏字典的构造方式之一,采用OMP方法进行稀疏表示编码。demo为运行主程序。例子用于图像超分辨率重建
代码片段和文件信息
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% the K-SVD basis is selected as the sparse representation dictionary
% the OMP algorithm is used to recover the image
% Author: zhang ben ncuzhangben@qq.com
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%***************************** read in the image **************************
img=imread(‘lena.bmp‘);
img=rgb2gray(img);% read in the image “lena.bmp“
img=double(img);
[Nn]=size(img);
img0 = img; % keep an original copy of the input signal
%****************form the measurement matrix and Dictionary ***************
%form the measurement matrix Phi
Phi=randn(Nn);
Phi = Phi./repmat(sqrt(sum(Phi.^21))[N1]); % normalize each column
%fix the parameters
param.L =20; % number of elements in each linear combination.
param.K =150; %number of dictionary elements
param.numIteration = 50; % number of iteration to execute the K-SVD
属性 大小 日期 时间 名称
----------- --------- ---------- ----- ----
文件 2199 2017-09-14 15:45 k-svd\demo.m
文件 12776 2017-09-14 15:36 k-svd\KSVD.m
文件 786486 2014-09-28 03:10 k-svd\lena.bmp
文件 1147 2017-09-14 14:42 k-svd\OMP.m
目录 0 2017-09-14 16:16 k-svd
----------- --------- ---------- ----- ----
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