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

01.09.2019

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

verfasst von: Abdelhak Bouhali, Daoud Berkani

Erschienen in: Automatic Control and Computer Sciences | Ausgabe 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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Metadaten
Titel
MAD-based Estimation of the Noise Level in the Contourlet Domain
verfasst von
Abdelhak Bouhali
Daoud Berkani
Publikationsdatum
01.09.2019
Verlag
Pleiades Publishing
Erschienen in
Automatic Control and Computer Sciences / Ausgabe 5/2019
Print ISSN: 0146-4116
Elektronische ISSN: 1558-108X
DOI
https://doi.org/10.3103/S0146411619050055

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