Title: 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.