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Proceedings Paper

Vector anisotropic filter for multispectral image denoising
Author(s): Ahmed Ben Said; Sebti Foufou; Rachid Hadjidj
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Paper Abstract

In this paper, we propose an approach to extend the application of anisotropic Gaussian filtering for multi- spectral image denoising. We study the case of images corrupted with additive Gaussian noise and use sparse matrix transform for noise covariance matrix estimation. Specifically we show that if an image has a low local variability, we can make the assumption that in the noisy image, the local variability originates from the noise variance only. We apply the proposed approach for the denoising of multispectral images corrupted by noise and compare the proposed method with some existing methods. Results demonstrate an improvement in the denoising performance.

Paper Details

Date Published: 30 April 2015
PDF: 8 pages
Proc. SPIE 9534, Twelfth International Conference on Quality Control by Artificial Vision 2015, 95340N (30 April 2015); doi: 10.1117/12.2182746
Show Author Affiliations
Ahmed Ben Said, Le2i, CNRS, Univ. de Bourgogne (France)
Qatar Univ. (Qatar)
Sebti Foufou, Qatar Univ. (Qatar)
Rachid Hadjidj, Qatar Univ. (Qatar)


Published in SPIE Proceedings Vol. 9534:
Twelfth International Conference on Quality Control by Artificial Vision 2015
Fabrice Meriaudeau; Olivier Aubreton, Editor(s)

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