Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/657142
Title: Edge Detector for Polarimetric SAR Images Using SIRV Model and Gauss-Shaped Filter
Authors: Deliang Xiang;Yifang Ban;Wei Wang;Tao Tang;Yi Su
subject: polarimetric synthetic aperture radar (PolSAR)|Gauss-shaped filter|spherically invariant random vector (SIRV)|urban areas|Edge detection
Year: 2016
Publisher: IEEE
Abstract: The classic constant false alarm rate edge detector with a rectangle-shaped filter has been proven to be effective and widely used in polarimetric synthetic aperture radar (PolSAR) images. However, in practical use, the assumption of complex Wishart distribution is often not respected, particularly in heterogeneous urban areas. In addition, as a simple smoothing filter, the rectangle-shaped window is often shown to be easy to incur false edge pixels near true edges. Therefore, its performance is limited. To overcome this restriction, we propose a new edge detector for PolSAR images, which utilizes the spherically invariant random vector product model to estimate the normalized covariance matrix for each pixel, and then replace the rectangle-shaped filter with a Gauss-shaped filter. The performance of our proposed methodology is presented and analyzed on two real PolSAR data sets, and the results show that the new edge detector attains better performance than the classic one, particularly for urban areas.
URI: http://localhost/handle/Hannan/169854
http://localhost/handle/Hannan/657142
ISSN: 1545-598X
1558-0571
volume: 13
issue: 11
Appears in Collections:2016

Files in This Item:
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7558164.pdf2.92 MBAdobe PDFThumbnail
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Title: Edge Detector for Polarimetric SAR Images Using SIRV Model and Gauss-Shaped Filter
Authors: Deliang Xiang;Yifang Ban;Wei Wang;Tao Tang;Yi Su
subject: polarimetric synthetic aperture radar (PolSAR)|Gauss-shaped filter|spherically invariant random vector (SIRV)|urban areas|Edge detection
Year: 2016
Publisher: IEEE
Abstract: The classic constant false alarm rate edge detector with a rectangle-shaped filter has been proven to be effective and widely used in polarimetric synthetic aperture radar (PolSAR) images. However, in practical use, the assumption of complex Wishart distribution is often not respected, particularly in heterogeneous urban areas. In addition, as a simple smoothing filter, the rectangle-shaped window is often shown to be easy to incur false edge pixels near true edges. Therefore, its performance is limited. To overcome this restriction, we propose a new edge detector for PolSAR images, which utilizes the spherically invariant random vector product model to estimate the normalized covariance matrix for each pixel, and then replace the rectangle-shaped filter with a Gauss-shaped filter. The performance of our proposed methodology is presented and analyzed on two real PolSAR data sets, and the results show that the new edge detector attains better performance than the classic one, particularly for urban areas.
URI: http://localhost/handle/Hannan/169854
http://localhost/handle/Hannan/657142
ISSN: 1545-598X
1558-0571
volume: 13
issue: 11
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7558164.pdf2.92 MBAdobe PDFThumbnail
Preview File
Title: Edge Detector for Polarimetric SAR Images Using SIRV Model and Gauss-Shaped Filter
Authors: Deliang Xiang;Yifang Ban;Wei Wang;Tao Tang;Yi Su
subject: polarimetric synthetic aperture radar (PolSAR)|Gauss-shaped filter|spherically invariant random vector (SIRV)|urban areas|Edge detection
Year: 2016
Publisher: IEEE
Abstract: The classic constant false alarm rate edge detector with a rectangle-shaped filter has been proven to be effective and widely used in polarimetric synthetic aperture radar (PolSAR) images. However, in practical use, the assumption of complex Wishart distribution is often not respected, particularly in heterogeneous urban areas. In addition, as a simple smoothing filter, the rectangle-shaped window is often shown to be easy to incur false edge pixels near true edges. Therefore, its performance is limited. To overcome this restriction, we propose a new edge detector for PolSAR images, which utilizes the spherically invariant random vector product model to estimate the normalized covariance matrix for each pixel, and then replace the rectangle-shaped filter with a Gauss-shaped filter. The performance of our proposed methodology is presented and analyzed on two real PolSAR data sets, and the results show that the new edge detector attains better performance than the classic one, particularly for urban areas.
URI: http://localhost/handle/Hannan/169854
http://localhost/handle/Hannan/657142
ISSN: 1545-598X
1558-0571
volume: 13
issue: 11
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7558164.pdf2.92 MBAdobe PDFThumbnail
Preview File