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:
 E. Luo, S. H. Chan, and T. Q. Nguyen, "Adaptive Image Denoising by Mixture Adaptation," IEEE Trans. Image Process. 2016.
 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.
Enming Luo (2021). Adaptive Image Denoising by Mixture Adaptation (EM adaptation) (https://www.mathworks.com/matlabcentral/fileexchange/58166-adaptive-image-denoising-by-mixture-adaptation-em-adaptation), MATLAB Central File Exchange. Retrieved .
Find the treasures in MATLAB Central and discover how the community can help you!Start Hunting!