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Title: Despeckling PolSAR images with a structure tensor filter
Authors: Santana Cedres, Daniel Elias 
Gomez, Luis 
Alvarez, Luis 
Frery, Alejandro C. 
UNESCO Clasification: 220990 Tratamiento digital. Imágenes
120326 Simulación
120602 Ecuaciones diferenciales
Keywords: Despeckling
Monte Carlo
Structure tensor
Synthetic aperture radar polarimetry
Issue Date: 2020
Journal: IEEE Geoscience and Remote Sensing Letters 
Abstract: In this letter, we propose a new despeckling filter for fully polarimetric synthetic aperture radar (PolSAR) images defined by 3 x 3 complex Wishart distributions. We first generalize the well-known structure tensor to deal with PolSAR data which allows to efficiently measure the dominant direction and contrast of edges. The generalization includes stochastic distances defined in the space of the Wishart matrices. Then, we embed the formulation into an anisotropic diffusion-like schema to build a filter able to reduce speckle and preserve edges. We evaluate its performance through an innovative experimental setup that also includes Monte Carlo analysis. We compare the results with a state-of-the-art polarimetric filter.
ISSN: 1545-598X
DOI: 10.1109/LGRS.2019.2919452
Source: IEEE Geoscience And Remote Sensing Letters [ISSN 1545-598X], v. 17 (2), p. 357-361, (Febrero 2020)
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