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PolSAR time series processing with Binary Partition Trees

机译:使用二进制分区树进行polsaR时间序列处理

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摘要

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.
机译:本文讨论极化合成孔径雷达(SAR)时间序列的处理。考虑了处理数据的时间维度的不同方法,这些方法是从该维度的不同目标特征中得出的。这些方法是定义两个不同的二进制分区树(BPT)结构的基础,这些结构用于SAR极化(PolSAR)数据处理。构造完成后,将BPT通过树木修剪进行处理,产生一组时空均匀区域,并估计其中的极化响应。证明了所提出的技术在不引入偏差或失真的情况下在时域中保留了PolSAR信息。另外,还分析了时间维度上数据的演变,并定义了获得基于BPT的场景变化图的技术。最后,提出的技术用于处理两个真实的RADARSAT-2数据集。

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