Nonparametric methods for detecting change in Multitemporal SAR/PolSAR Satellite Data
Applications
2020-01-17 v1
Abstract
We employ nonparametric statistical procedures to analyse multitemporal SAR/PolSAR satellite images. The aim is two-fold. We seek parsimony in data representation as well as efficient change detection. For these, wavelets and geostatistical analyses are applied to the images (Morettin et al., 2017; Krainski et al., 2018). Following this representation, the dimension of the underlying generating process is estimated (Fonseca and Pinheiro, 2019), and a set of multivariate characteristics is extracted. Change-points are then detected via wavelets (Montoril et al., 2019).
Keywords
Cite
@article{arxiv.2001.05764,
title = {Nonparametric methods for detecting change in Multitemporal SAR/PolSAR Satellite Data},
author = {Rodney Fonseca and Guilherme Ludwig and Michel Montoril and Aluísio Pinheiro},
journal= {arXiv preprint arXiv:2001.05764},
year = {2020}
}
Comments
5 pages, 3 figures