Low-rankness transfer for denoising Sentinel-1 SAR images

Abstract : This paper introduces a new algorithm for denoising SAR images. It is directly applicable to Sentinel-1 GRD images, without the need for single-look complex operations. The algorithm builds on the non-local patch matching idea for statistical denoising, similar to the SAR-BM3D and NL-SAR algorithms, but introduces two corrections : 1. A non-uniform prior for the reflectance values is used for the patch matching, thus allowing a better fit to the data, and 2. Denoising is performed in singular values space, with a prior distribution of expected "clean" singular values learned and transfered from optical images. The denoised SAR images show reduced amount of speckle compared to alternative methods.
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Submitted on : Tuesday, November 27, 2018 - 1:15:22 PM
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  • HAL Id : hal-01936331, version 1



Nicolas Brodu. Low-rankness transfer for denoising Sentinel-1 SAR images. ISIVC'2018 - 9th International Symposium on Signal, Image, Video and Communications, Nov 2018, Rabat, Morocco. ⟨hal-01936331⟩



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