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PolSAR Time Series Processing With Binary Partition Trees
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DOI：10.1109/TGRS.2013.2273664.png)
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摘要
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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 spatio-temporal 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.
Keyword:
Binary partition tree (BPT)
change detection
synthetic aperture radar (SAR) polarimetry
segmentation
time series
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期刊
IF:
8.6
论文数:
2.1W
被引数:
10.7W
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分享收藏Processing Multidimensional SAR and Hyperspectral Images With Binary Partition Tree.png)
PROCEEDINGS OF THE IEEE
PROCEEDINGS OF THE IEEEIF25.9
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