MuLoG, or How to apply Gaussian denoisers to multi-channel SAR speckle reduction?
Charles-Alban Deledalle (IMB), Loïc Denis (LHC), Sonia Tabti (GREYC, LTCI), Florence Tupin (LTCI)
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.
Subjects: Statistics Theory (math.ST); Applications (stat.AP)
Cite as: arXiv:1704.05335 [math.ST]
(or arXiv:1704.05335v1 [math.ST] for this version)