DocumentCode :
39138
Title :
Multidate Divergence Matrices for the Analysis of SAR Image Time Series
Author :
Atto, Abdourrahmane M. ; Trouve, E. ; Berthoumieu, Yannick ; Mercier, Guillaume
Author_Institution :
LISTIC - Polytech Annecy-Chambéry, Université de Savoie, Annecy le Vieux Cedex, France
Volume :
51
Issue :
4
fYear :
2013
fDate :
Apr-13
Firstpage :
1922
Lastpage :
1938
Abstract :
The paper provides a spatio-temporal change detection framework for the analysis of image time series. In this framework, the detection of changes in time is addressed at the image level by using a matrix of cross-dissimilarities computed upon wavelet and curvelet image features. This makes possible identifying the acquisitions of interest: the acquisitions that exhibit singular behavior with respect to their neighborhood in the time series, and those that are representatives of some stationary behavior. These acquisitions of interest are compared at the pixel level to detect spatial changes characterizing the evolution of the time series. Experiments carried out over European Remote Sensing (ERS) and TerraSAR-X time series highlight the relevancy of the approach for analyzing synthetic aperture radar image time series.
Keywords :
Approximation methods; Dictionaries; Feature extraction; Parametric statistics; Synthetic aperture radar; Time series analysis; Transforms; Change detection; Kullback–Leibler (KL) divergence; curvelets; image time series; parametric modeling; wavelets;
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
Publisher :
ieee
ISSN :
0196-2892
Type :
jour
DOI :
10.1109/TGRS.2012.2210228
Filename :
6295651
Link To Document :
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