文件名称:k-svd-codeappt
介绍说明--下载内容均来自于网络,请自行研究使用
内含用matlab编写的k-svd算法代码.可以对图像进行稀疏分解,另附ppt对ksvd进行理论学习-Includes using matlab k-svd algorithm code. Images can be sparse decomposition, attached ppt theoretical study of ksvd
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下载文件列表
k-svd算法m代码.用于形成冗余字典,对图像进行稀疏分解\K-SVDppt.zip
...................................................\k_svd\11.gif
...................................................\.....\barbara.png
...................................................\.....\boat.png
...................................................\.....\demo1.m
...................................................\.....\demo2.m
...................................................\.....\demo3.m
...................................................\.....\denoiseImageDCT.m
...................................................\.....\denoiseImageGlobal.m
...................................................\.....\denoiseImageKSVD.asv
...................................................\.....\denoiseImageKSVD.m
...................................................\.....\displayDictionaryElementsAsImage.asv
...................................................\.....\displayDictionaryElementsAsImage.m
...................................................\.....\gererateSyntheticDictionaryAndData.m
...................................................\.....\globalTrainedDictionary.mat
...................................................\.....\house.png
...................................................\.....\KSVD.asv
...................................................\.....\KSVD.m
...................................................\.....\...._Matlab_ToolBox\barbara.png
...................................................\.....\...................\boat.png
...................................................\.....\...................\demo1.m
...................................................\.....\...................\demo2.m
...................................................\.....\...................\demo3.m
...................................................\.....\...................\denoiseImageDCT.m
...................................................\.....\...................\denoiseImageGlobal.m
...................................................\.....\...................\denoiseImageKSVD.m
...................................................\.....\...................\displayDictionaryElementsAsImage.asv
...................................................\.....\...................\displayDictionaryElementsAsImage.m
...................................................\.....\...................\gererateSyntheticDictionaryAndData.m
...................................................\.....\...................\globalTrainedDictionary.mat
...................................................\.....\...................\house.png
...................................................\.....\...................\KSVD.m
...................................................\.....\...................\KSVD_NN.m
...................................................\.....\...................\lena.png
...................................................\.....\...................\MOD.m
...................................................\.....\...................\my_im2col.m
...................................................\.....\...................\NN_BP.m
...................................................\.....\...................\OMP.m
...................................................\.....\...................\OMPerr.m
...................................................\.....\...................\peppers256.png
...................................................\.....\...................\README.txt
...................................................\.....\KSVD_NN.m
...................................................\.....\lena.png
...................................................\.....\MOD.m
...................................................\.....\my_im2col.asv
...................................................\.....\my_im2col.m
...................................................\.....\NN_BP.m
...................................................\.....\OMP.asv
...................................................\.....\OMP.m
...................................................\.....\OMPerr.m
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