Title:
LowPatchRank_regularization
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Description: For periodic texture images with noise, a new method based on two dimensional rank constraint is proposed. This method combines the theory and method of total variation denoising, and uses the characteristic of the low rank of the image to carry on the low rank constraint. By comparing with the total variation denoising method, we can know that the mixed regularization method can effectively separate the noise the periodic texture image, and the image can be well maintained. Even if the non strict periodic texture, this method still has the very good denoising effect.
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File list (Check if you may need any files):
New_regularization\barb.png
..................\Breg_GS_Iter.asv
..................\Breg_GS_Iter.m
..................\Breg_GS_Iter1.asv
..................\Breg_GS_Iter1.m
..................\Breg_Var_Iter.asv
..................\Breg_Var_Iter.m
..................\inv_P.m
..................\lena.png
..................\LowPatchRank_TV.asv
..................\LowPatchRank_TV.m
..................\normalization.m
..................\norm_two.m
..................\P_mapping.m
..................\rank.jpg
..................\shrink.asv
..................\shrink.m
..................\svt.asv
..................\svt.m
..................\toys.bmp
New_regularization
