CHANGE DETECTION IN MULTITEMPORAL HR SAR IMAGES: A HYPOTHESIS TEST-BASED APPROACH

Author(s)

Horta, Michelle M. ; Mascarenhas, Nelson D. A. ; Sportouche, H. ; Seichepine, N. ; Tupin, F. ; Nicolas, J. -M. ; IEEE

• Document type: Journal article
• Source: 2012 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS); v. N/A, p. 4-pg., 2012-01-01.

Abstract

Starting with a comparison of state of the art criteria and the influence of filtering, this paper presents an analysis tool for multi-temporal SAR images. It is based on the detection of a step change pattern with a generalized maximum likelihood ratio test. Compared to previous works on similar subject, the proposed approach takes into account a filtering step by a non-local approach and a spatially varying equivalent number of looks. Performance analysis is first done on synthetic data and then results on a real data set are analyzed. (AU)

• FAPESP's process: 09/14270-4 - Classification of fully polarimetric SAR images using the finite mixture models with semi-supervised learning and bayesian inference
• Grantee: Michelle Matos Horta Tenca
• Support Opportunities: Scholarships in Brazil - Post-Doctoral