Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/626702
Title: Modified Statistically Homogeneous Pixels&x2019; Selection With Multitemporal SAR Images
Authors: Yingjie Wang;Yunkai Deng;Wenbo Fei;Robert Wang;Huina Song;Jili Wang;Ning Li
subject: Anderson–Darling (AD) test|interferometric filtering|coherence estimation|K-means|statistically homogeneous pixels (SHPs)
Year: 2016
Publisher: IEEE
Abstract: Statistically homogeneous pixels (SHPs) are considerably significant in many interferometric applications, such as interferometric filtering, distributed scatterer selection, small baseline subset, and SqueeSAR processing. It is very important to achieve SHPs efficiently and accurately. Previous studies on SHPs' selection are based on spatial restrictions and likelihood ratio test, such as Lee filtering, Kolmogorov-Smirnov test, and Anderson-Darling test. However, these algorithms do not stand up to test for the spatial similarity hypothesis for complex terrains with a few images. To solve the problems, this letter proposes a modified SHPs' selection algorithm. It utilizes geometric distance and target features for reaching a priori information to help the similarity hypothesis tests. The proposed algorithm has been tested on simulated and real data to prove the improvements in terms of accuracy and computational efficiency.
URI: http://localhost/handle/Hannan/145681
http://localhost/handle/Hannan/626702
ISSN: 1545-598X
1558-0571
volume: 13
issue: 12
Appears in Collections:2016

Files in This Item:
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7740009.pdf1.09 MBAdobe PDFThumbnail
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Title: Modified Statistically Homogeneous Pixels&x2019; Selection With Multitemporal SAR Images
Authors: Yingjie Wang;Yunkai Deng;Wenbo Fei;Robert Wang;Huina Song;Jili Wang;Ning Li
subject: Anderson–Darling (AD) test|interferometric filtering|coherence estimation|K-means|statistically homogeneous pixels (SHPs)
Year: 2016
Publisher: IEEE
Abstract: Statistically homogeneous pixels (SHPs) are considerably significant in many interferometric applications, such as interferometric filtering, distributed scatterer selection, small baseline subset, and SqueeSAR processing. It is very important to achieve SHPs efficiently and accurately. Previous studies on SHPs' selection are based on spatial restrictions and likelihood ratio test, such as Lee filtering, Kolmogorov-Smirnov test, and Anderson-Darling test. However, these algorithms do not stand up to test for the spatial similarity hypothesis for complex terrains with a few images. To solve the problems, this letter proposes a modified SHPs' selection algorithm. It utilizes geometric distance and target features for reaching a priori information to help the similarity hypothesis tests. The proposed algorithm has been tested on simulated and real data to prove the improvements in terms of accuracy and computational efficiency.
URI: http://localhost/handle/Hannan/145681
http://localhost/handle/Hannan/626702
ISSN: 1545-598X
1558-0571
volume: 13
issue: 12
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7740009.pdf1.09 MBAdobe PDFThumbnail
Preview File
Title: Modified Statistically Homogeneous Pixels&x2019; Selection With Multitemporal SAR Images
Authors: Yingjie Wang;Yunkai Deng;Wenbo Fei;Robert Wang;Huina Song;Jili Wang;Ning Li
subject: Anderson–Darling (AD) test|interferometric filtering|coherence estimation|K-means|statistically homogeneous pixels (SHPs)
Year: 2016
Publisher: IEEE
Abstract: Statistically homogeneous pixels (SHPs) are considerably significant in many interferometric applications, such as interferometric filtering, distributed scatterer selection, small baseline subset, and SqueeSAR processing. It is very important to achieve SHPs efficiently and accurately. Previous studies on SHPs' selection are based on spatial restrictions and likelihood ratio test, such as Lee filtering, Kolmogorov-Smirnov test, and Anderson-Darling test. However, these algorithms do not stand up to test for the spatial similarity hypothesis for complex terrains with a few images. To solve the problems, this letter proposes a modified SHPs' selection algorithm. It utilizes geometric distance and target features for reaching a priori information to help the similarity hypothesis tests. The proposed algorithm has been tested on simulated and real data to prove the improvements in terms of accuracy and computational efficiency.
URI: http://localhost/handle/Hannan/145681
http://localhost/handle/Hannan/626702
ISSN: 1545-598X
1558-0571
volume: 13
issue: 12
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7740009.pdf1.09 MBAdobe PDFThumbnail
Preview File