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Adaptive Image Denoising by Mixture Adaptation (EM adaptation)

version 1.0 (10.6 MB) by Enming Luo
An EM adaptation method to learn effective image priors for image denoising

3 Downloads

Updated 11 Jul 2016

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This package provides an implementation of an adaptive image denoising algorithm by mixture adaptation. The proposed method [1, 2] takes a generic prior learned from a generic external database and adapts it to the noisy image to generate a specific prior, which is then used for MAP denoising. The proposed algorithm is rigorously derived
from the Bayesian hyper-prior perspective and is further simplified to reduce the computational complexity. To have an overall evaluation of the denoising performance, please run the demo file: "demo.m". For additional information and citations, please refer to:
[1] E. Luo, S. H. Chan, and T. Q. Nguyen, "Adaptive Image Denoising by Mixture Adaptation," IEEE Trans. Image Process. 2016.
[2] S. H. Chan, E. Luo and T. Q. Nguyen, "Adaptive Patch-based Image Denoising by EM-adaptation," in Proc. IEEE Global Conf. Signal Information Process. (GlobalSIP'15), Dec. 2015.

Comments and Ratings (1)

Enming Luo

All the codes could also be found here: videoprocessing.ucsd.edu/~eluo

MATLAB Release Compatibility
Created with R2013a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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