Description: It firstly get the redundant dictionary of a noised image by dictionary learning.Then,the image patches are gathered according to their similarities.Meanwhile,the similar patches get sparse representation showed in dictionaries by iterative shrinkage and L1 regularization constraints and eventually the image is restored and noise is removed.The experimental results indicate that the proposed algorithm can well preserve the structure information of the common image with a higher Peak Signal to Noise Ratio(PNSR),compared with state-of-the-art algorithms,such as K-SVD and BM3D
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File list (Check if you may need any files):
CSR_Denoising
.............\Data
.............\....\images
.............\....\......\barbara.tif
.............\....\......\boat.tif
.............\....\......\cameraman.tif
.............\....\......\couple.tif
.............\....\......\fingerprint.tif
.............\....\......\hill.tif
.............\....\......\house.tif
.............\....\......\Lena512.tif
.............\....\......\man.tif
.............\....\......\Monarch_full.tif
.............\....\......\peppers256.tif
.............\....\......\straw.tif
.............\....\......\textures
.............\....\......\........\hex.tif
.............\Denoising_Main.m
.............\Results
.............\.......\Denoising_results
.............\.......\.................\nsig_20
.............\.......\.................\.......\CSR_de_PSNR_SSIM.txt
.............\.......\.................\.......\PCA_CSR_PSNR_SSIM.txt
.............\Utilities
.............\.........\Add_noise.m
.............\.........\cal_ssim.m
.............\.........\Clustering_PCA_New.m
.............\.........\csnr.m
.............\.........\CSR_Denoising.m
.............\.........\CSR_Thresholding.m
.............\.........\ext_im.m
.............\.........\find_blks.m
.............\.........\find_blks_fast.m
.............\.........\find_blks_fast2.m
.............\.........\getpca.m
.............\.........\Image_Denoising.m
.............\.........\Proc_cls_idx.m
.............\.........\Set_PCA_idx.m
.............\.........\soft.m
.............\.........\Soft_PCA.m
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