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Proceedings Paper

Change detection of polarimetric SAR images based on the KummerU Distribution
Author(s): Quan Chen; Pengfei Zou; Zhen Li; Ping Zhang
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Paper Abstract

In the society of PolSAR image segmentation, change detection and classification, the classical Wishart distribution has been used for a long time, but it especially suit to low-resolution SAR image, because in traditional sensors, only a small number of scatterers are present in each resolution cell. With the improving of SAR systems these years, the classical statistical models can therefore be reconsidered for high resolution and polarimetric information contained in the images acquired by these advanced systems. In this study, SAR image segmentation algorithm based on level-set method, added with distance regularized level-set evolution (DRLSE) is performed using Envisat/ASAR single-polarization data and Radarsat-2 polarimetric images, respectively. KummerU heterogeneous clutter model is used in the later to overcome the homogeneous hypothesis at high resolution cell. An enhanced distance regularized level-set evolution (DRLSE-E) is also applied in the later, to ensure accurate computation and stable level-set evolution. Finally, change detection based on four polarimetric Radarsat-2 time series images is carried out at Genhe area of Inner Mongolia Autonomous Region, NorthEastern of China, where a heavy flood disaster occurred during the summer of 2013, result shows the recommend segmentation method can detect the change of watershed effectively.

Paper Details

Date Published: 8 November 2014
PDF: 7 pages
Proc. SPIE 9260, Land Surface Remote Sensing II, 92603V (8 November 2014); doi: 10.1117/12.2069198
Show Author Affiliations
Quan Chen, Institute of Remote Sensing and Digital Earth (China)
Pengfei Zou, Institute of Remote Sensing and Digital Earth (China)
Univ. of Chinese Academy of Sciences (China)
Zhen Li, Institute of Remote Sensing and Digital Earth (China)
Ping Zhang, Institute of Remote Sensing and Digital Earth (China)


Published in SPIE Proceedings Vol. 9260:
Land Surface Remote Sensing II
Thomas J. Jackson; Jing Ming Chen; Peng Gong; Shunlin Liang, Editor(s)

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