MuLoG, or How to apply Gaussian denoisers to multi-channel SAR speckle reduction? - Archive ouverte HAL Access content directly
Journal Articles IEEE Transactions on Image Processing Year : 2017

MuLoG, or How to apply Gaussian denoisers to multi-channel SAR speckle reduction?

Abstract

Speckle reduction is a longstanding topic in synthetic aperture radar (SAR) imaging. Since most current and planned SAR imaging satellites operate in polarimetric, interferometric or tomographic modes, SAR images are multi-channel and speckle reduction techniques must jointly process all channels to recover polarimetric and interferometric information. The distinctive nature of SAR signal (complex-valued, corrupted by multiplicative fluctuations) calls for the development of specialized methods for speckle reduction. Image denoising is a very active topic in image processing with a wide variety of approaches and many denoising algorithms available, almost always designed for additive Gaussian noise suppression. This paper proposes a general scheme, called MuLoG (MUlti-channel LOgarithm with Gaussian denoising), to include such Gaussian denoisers within a multi-channel SAR speckle reduction technique. A new family of speckle reduction algorithms can thus be obtained, benefiting from the ongoing progress in Gaussian denoising, and offering several speckle reduction results often displaying method-specific artifacts that can be dismissed by comparison between results.
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Dates and versions

hal-01388858 , version 1 (27-10-2016)
hal-01388858 , version 2 (12-04-2017)

Identifiers

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Charles-Alban Deledalle, Loïc Denis, Sonia Tabti, Florence Tupin. MuLoG, or How to apply Gaussian denoisers to multi-channel SAR speckle reduction?. IEEE Transactions on Image Processing, 2017, 26 (9), pp.4389-4403. ⟨10.1109/TIP.2017.2713946⟩. ⟨hal-01388858v2⟩
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