Ratio-based similarity criteria for polarimetric SAR image

H. Aghababaei, G. Ferraioli, V. Pascazio

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

Dealing with multi-look polarimetric synthetic aperture radar (PolSAR) images requires averaging several independent looks to generate a sample covariance matrix of similar target scattering vectors. Along this, estimation of optimal similarity between target scattering vectors is still an open issue. In the literature, this intrinsic task has been mainly addressed in the information-based, geometric-based and detection-based frameworks. However, the derived measures mainly rely on the model assumption such as fully developed speckle and circular complex Gaussian distribution of the scattering vectors, which may not be held in high-resolution images of urban environments. To cope with this possible issue a discriminative model-free measure is proposed, where the similarity of target scattering is computed in the framework of non-local or patch based algorithm. In particular, the discriminative measure is constructed using the ratio between two pre-estimated covariance matrices of the scattering vectors. Experimental validation of the proposed measure is provided using ALOS-PALSAR image and compared with existing criterions in the literature.

Original languageEnglish
Title of host publication2020 IEEE Latin American GRSS and ISPRS Remote Sensing Conference, LAGIRS 2020
Subtitle of host publicationProceedings
PublisherIEEE
Pages318-321
Number of pages4
ISBN (Electronic)9781728143507
DOIs
Publication statusPublished - 22 Mar 2020
Event2020 IEEE Latin American GRSS and ISPRS Remote Sensing Conference, LAGIRS 2020 - Universidad de Chile, Santiago, Chile
Duration: 22 Mar 202026 Mar 2020

Conference

Conference2020 IEEE Latin American GRSS and ISPRS Remote Sensing Conference, LAGIRS 2020
Abbreviated titleLAGIRS 2020
CountryChile
CitySantiago
Period22/03/2026/03/20

Keywords

  • Non Local Filters
  • Polarimetric SAR image
  • Ratio Image
  • Similarity criterion

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