This package provides an implementation of an adaptive image denoising algorithm using targeted databases. The proposed method [1, 2], called Targeted Image Denoising (TID), applies a group sparsity minimization and a localized prior to learn the optimal denoising filter from the targeted database. To have an overall evaluation of the denoising performance, please run the demo file: "demo.m". For comparison purposes, we also provide the codes for some state-of-the-art denoising methods including BM3D, BM3D-PCA, LPG-PCA, and NLM. All these methods are re-implemented and modified by us such that patch search is performed over the targeted external databases.
For additional information and citations, please refer to:
 E. Luo, S. H. Chan, and T. Q. Nguyen, "Adaptive Image Denoising by Targeted Databases," IEEE Trans. Image Process., vol. 24, no. 7, pp. 2167-2181, Jul. 2015.
 E. Luo, S. H. Chan, and T. Q. Nguyen, "Image Denoising by Targeted External Databases," in Proc. IEEE Intl. Conf. on Acoustics, Speech and Signal Process.(ICASSP'14), pp. 2469-2473, May 2014.
Hi, I am a little bit confused for the variables "rem_h" and "rem_w" in some scripts.
@lydia hamis and @Mohammad Mahdi Abedi, in the code, if you need to recompile the code to generate the .mex files, you could uncommented some lines at the very beginning (It should be pretty easy). I think I have provided the .mex files but in case you couldn't find them, you could also download all the codes here: videoprocessing.ucsd.edu/~eluo
hi.. i try to tun your program..but i encountered with this error..can you please help me out?
Error using mex
No supported compiler or SDK was found. You can install the freely available MinGW-w64 C/C++ compiler; see Install MinGW-w64 Compiler. For more options,
Error in demo (line 20)
mex -g code/blk_matching.cpp;
Hello can you help me with the compiler error:
Error using mex
No supported compiler or SDK was found. For options, visit
I have the 2015a version
Great toolbox for image denoising!
Great implementation for image denoising.
The package contains reliable tools for image denoising. A big appreciation for the effort paid by the author.
Nice implementation easy to use.
Well written code with other references
Great tool, very easy to use
A nice toolbox for image denoising~
Thank you for sharing!
nice documented, easy to follow
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