Patch-based image denoising: Probability distribution estimation vs. sparsity prior (bibtex)
by Dai Viet, Sébastien Li-Thiao-Té, Marie Luong, T. Le-Tien and Françoise Dibos
Reference:
D. Viet, S. Li-Thiao-Té, M. Luong, T. Le-Tien, F. Dibos, "Patch-based image denoising: Probability distribution estimation vs. sparsity prior", in 2017 25th European Signal Processing Conference (EUSIPCO), pp. 1490-1494.
Bibtex Entry:
@INPROCEEDINGS{8081457,
author={Dai Viet  and Sébastien Li-Thiao-Té and Marie Luong and T. Le-Tien and Françoise Dibos},
booktitle={2017 25th European Signal Processing Conference (EUSIPCO)},
title={Patch-based image denoising: Probability distribution estimation vs. sparsity prior},
year={2017},
volume={},
number={},
pages={1490-1494},
keywords={Bayes methods;image denoising;image reconstruction;image representation;probability;Bayesian framework;estimated probability distribution;good quality images;image formation model;image patches;patch-based image denoising;prior image distribution;probability distribution estimation;sparsity approach;Databases;Dictionaries;Estimation;Noise measurement;Noise reduction;Probability distribution;Standards;Patch-based;denoising;probability distribution estimation;sparse representation},
doi={10.23919/EUSIPCO.2017.8081457},
ISSN={},
month={Aug.},
l2ti-category  = {intc},
}
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