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 |
SCOPUSTM
Citations
3
checked on Nov 24, 2024
WEB OF SCIENCETM
Citations
1
checked on Feb 25, 2024
Page view(s)
124
checked on Aug 24, 2024
Google ScholarTM
Check
Altmetric
Share
Export metadata
Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.