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Proceedings Paper

Fast and accurate denoising method applied to very high resolution optical remote sensing images
Author(s): Antoine Masse; Sébastien Lefèvre; Renaud Binet; Stéphanie Artigues; Pierre Lassalle; Gwendoline Blanchet; Simon Baillarin
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Paper Abstract

Restoration of Very High Resolution (VHR) optical Remote Sensing Image (RSI) is critical and leads to the problem of removing instrumental noise while keeping integrity of relevant information. Improving denoising in an image processing chain implies increasing image quality and improving performance of all following tasks operated by experts (photo-interpretation, cartography, etc.) or by algorithms (land cover mapping, change detection, 3D reconstruction, etc.). In a context of large industrial VHR image production, the selected denoising method should optimized accuracy and robustness with relevant information and saliency conservation, and rapidity due to the huge amount of data acquired and/or archived. Very recent research in image processing leads to a fast and accurate algorithm called Non Local Bayes (NLB) that we propose to adapt and optimize for VHR RSIs. This method is well suited for mass production thanks to its best trade-off between accuracy and computational complexity compared to other state-of-the-art methods. NLB is based on a simple principle: similar structures in an image have similar noise distribution and thus can be denoised with the same noise estimation. In this paper, we describe in details algorithm operations and performances, and analyze parameter sensibilities on various typical real areas observed in VHR RSIs.

Paper Details

Date Published: 4 October 2017
PDF: 20 pages
Proc. SPIE 10427, Image and Signal Processing for Remote Sensing XXIII, 1042703 (4 October 2017); doi: 10.1117/12.2277705
Show Author Affiliations
Antoine Masse, Ctr. National d'Études Spatiales (France)
Sébastien Lefèvre, Univ. de Bretagne-Sud (France)
Renaud Binet, Ctr. National d'Études Spatiales (France)
Stéphanie Artigues, Ctr. National d'Études Spatiales (France)
Pierre Lassalle, Ctr. National d'Études Spatiales (France)
Gwendoline Blanchet, Ctr. National d'Études Spatiales (France)
Simon Baillarin, Ctr. National d'Études Spatiales (France)


Published in SPIE Proceedings Vol. 10427:
Image and Signal Processing for Remote Sensing XXIII
Lorenzo Bruzzone, Editor(s)

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