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Automatic Control and Computer Sciences
Published in: Automatic Control and Computer Sciences 5/2019

01-09-2019

MAD-based Estimation of the Noise Level in the Contourlet Domain

Authors: Abdelhak Bouhali, Daoud Berkani

Published in: Automatic Control and Computer Sciences | Issue 5/2019

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Abstract

Noise-level estimation remains one of the most critical issues related to the contourlet-based approaches. In this paper, an investigation of an effective solution is directed from any redundant contourlet expansion. This is going to be addressed for the first time in that domain. In this proposition, the noise level is estimated as the median absolute value (MAD) of the finest multi-scale coefficients, calibrated by three correction parameters. This is done according to some visual classification of the natural images. The present estimator provides a better compromise between the image and the contourlet expansion nature, which makes the estimation results more accurate for a wide range of natural images, when compared to the best state-of-the-art methods. Therefore, it is extensively recommended for most of the contourlet-based image applications (Thresholding, filtering, etc.) thanks to its accuracy, simplicity, and rapidity.
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Metadata
Title
MAD-based Estimation of the Noise Level in the Contourlet Domain
Authors
Abdelhak Bouhali
Daoud Berkani
Publication date
01-09-2019
Publisher
Pleiades Publishing
Published in
Automatic Control and Computer Sciences / Issue 5/2019
Print ISSN: 0146-4116
Electronic ISSN: 1558-108X
DOI
https://doi.org/10.3103/S0146411619050055

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