DocumentCode :
5386
Title :
PolSAR Time Series Processing With Binary Partition Trees
Author :
Alonso-Gonzalez, Alberto ; Lopez-Martinez, Carlos ; Salembier, Philippe
Author_Institution :
Dept. of Signal Theor. & Commun. (TSC), Tech. Univ. of Catalonia (UPC), Barcelona, Spain
Volume :
52
Issue :
6
fYear :
2014
fDate :
Jun-14
Firstpage :
3553
Lastpage :
3567
Abstract :
This paper deals with the processing of polarimetric synthetic aperture radar (SAR) time series. Different approaches to deal with the temporal dimension of the data are considered, which are derived from different target characterizations in this dimension. These approaches are the basis for defining two different binary partition tree (BPT) structures that are employed for SAR polarimetry (PolSAR) data processing. Once constructed, the BPT is processed by a tree pruning, producing a set of spatiotemporal homogeneous regions, and estimating the polarimetric response within them. It is demonstrated that the proposed technique preserves the PolSAR information in the spatial and the temporal domains without introducing bias nor distortion. Additionally, the evolution of the data in the temporal dimension is also analyzed, and techniques to obtain BPT-based scene change maps are defined. Finally, the proposed techniques are employed to process two real RADARSAT-2 data sets.
Keywords :
radar polarimetry; remote sensing by radar; synthetic aperture radar; BPT structures; BPT-based scene change maps; PolSAR data processing; PolSAR information; PolSAR time series processing; RADARSAT-2 data sets; SAR polarimetry data processing; binary partition trees; data temporal dimension; spatiotemporal homogeneous regions; synthetic aperture radar; target characterizations; tree pruning; Covariance matrices; Data models; Radar polarimetry; Speckle; Synthetic aperture radar; Time series analysis; Binary partition tree (BPT); change detection; segmentation; synthetic aperture radar (SAR) polarimetry; time series;
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
Publisher :
ieee
ISSN :
0196-2892
Type :
jour
DOI :
10.1109/TGRS.2013.2273664
Filename :
6595582
Link To Document :
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