Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/55713
Title: Local edginess measures in PolSAR imagery by using stochastic distances
Authors: Gómez Déniz, Luis 
Alvarez, Luis 
Frery, Alejandro C.
UNESCO Clasification: 120601 Construcción de algoritmos
120602 Ecuaciones diferenciales
220990 Tratamiento digital. Imágenes
Keywords: Edge Detector
Synthetic Aperture Radar Polarimetry
Structure Tensor
Edge Detection
Issue Date: 2018
Journal: IEEE International Geoscience and Remote Sensing Symposium proceedings 
Conference: IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2018) 
Abstract: In this paper we study the local behavior of Fully PolSAR (Polarimetric Synthetic Aperture Radar) images defined by 3 × 3 complex Wishart distributions. We propose a generalization of the well-known structure tensor to Fully PolSAR images, as well as a measure of the smoothness of such predominant direction. This measure provides local information as the predominant direction of maximum variation of the complex Wishart distribution in a neighborhood of an image domain point (x, y). We use stochastic distances defined in the space of Wishart matrices to generalize de structure tensor to PolSAR images. The study of the local behavior of PolSAR images address a number of processing and analysis problems. In particular, in this paper we apply this new approach to edge estimation using the magnitude of the PolSAR image variation provided by the generalized structure tensor. We also show promising results for simulated and actual PolSAR data.
URI: http://hdl.handle.net/10553/55713
ISBN: 9781538671504
ISSN: 2153-6996
DOI: 10.1109/IGARSS.2018.8518008
Source: IEEE International Geoscience and Remote Sensing Symposium proceedings [ISSN 2153-6996], p. 5796-5799, (2018)
Appears in Collections:Actas de congresos
Show full item record

SCOPUSTM   
Citations

2
checked on Mar 24, 2024

WEB OF SCIENCETM
Citations

1
checked on Feb 25, 2024

Page view(s)

90
checked on Nov 4, 2023

Google ScholarTM

Check

Altmetric


Share



Export metadata



Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.