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Paul Rodríguez, Renán Rojas and Brendt Wohlberg, "Mixed Gaussian-Impulse Noise Image Restoration via Total Variation", in Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), (Kyoto, Japan), doi:10.1109/ICASSP.2012.6288073, pp. 1077--1080, Mar 2012

Abstract

Several Total Variation (TV) regularization methods have recently been proposed to address denoising under mixed Gaussian and impulse noise. While achieving high-quality denoising results, these new methods are based on complicated cost functionals that are difficult to optimize, which affects their computational performance.

In this paper we propose a simple cost functional consisting of a TV regularization term and l2 and l1 data fidelity terms, for Gaussian and impulse noise respectively, with local regularization parameters selected by an impulse noise detector. The computational performance of the proposed algorithm greatly exceeds that of the state of the art algorithms within the TV framework, and its reconstruction quality performance is competitive for high noise levels, for both grayscale and vector-valued images.

BibTeX Entry

@inproceedings{rodriguez-2012-mixed,
author = {Paul Rodr\'{i}guez and Ren\'{a}n Rojas and Brendt Wohlberg},
title = {Mixed Gaussian-Impulse Noise Image Restoration via Total Variation},
year = {2012},
month = Mar,
urlpdf = {http://brendt.wohlberg.net/publications/pdf/rodriguez-2012-mixed},
booktitle = {Proceedings of IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP)},
address = {Kyoto, Japan},
doi = {10.1109/ICASSP.2012.6288073},
pages = {1077--1080}
}