Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/627013
Title: Pol-SAR Classification Based on Generalized Polar Decomposition of Mueller Matrix
Authors: Hanning Wang;Zhimin Zhou;John Turnbull;Qian Song;Feng Qi
subject: Mueller matrix|Generalized polar decomposition|roll-invariant parameters|polarimetric SAR classification
Year: 2016
Publisher: IEEE
Abstract: In this letter, we investigate an application of a generalized polar decomposition of the Mueller matrix for polarimetric synthetic aperture radar (Pol-SAR) classification. Six roll-invariant parameters (diattenuation, retardance, polarization power, depolarization anisotropy, depolarization power, and transmittance) are selected as features for the classification of scattering types. Experimental results using the AIRSAR data over Flevoland show that, for most field types, the D-R-A<sub>&#x0394;</sub>- &#x0394;-m<sub>00</sub> set provides the highest classification accuracy, followed by the D-R-P<sub>&#x0394;</sub>-&#x0394;-m<sub>00</sub> set which also provides better accuracy than the widely used H -&#x03B1;-(&#x03B4;-&#x03B3;)-A-span set. The proposed method would be valuable for Pol-SAR interpretation.
URI: http://localhost/handle/Hannan/157615
http://localhost/handle/Hannan/627013
ISSN: 1545-598X
1558-0571
volume: 13
issue: 4
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7419830.pdf1.77 MBAdobe PDFThumbnail
Preview File
Title: Pol-SAR Classification Based on Generalized Polar Decomposition of Mueller Matrix
Authors: Hanning Wang;Zhimin Zhou;John Turnbull;Qian Song;Feng Qi
subject: Mueller matrix|Generalized polar decomposition|roll-invariant parameters|polarimetric SAR classification
Year: 2016
Publisher: IEEE
Abstract: In this letter, we investigate an application of a generalized polar decomposition of the Mueller matrix for polarimetric synthetic aperture radar (Pol-SAR) classification. Six roll-invariant parameters (diattenuation, retardance, polarization power, depolarization anisotropy, depolarization power, and transmittance) are selected as features for the classification of scattering types. Experimental results using the AIRSAR data over Flevoland show that, for most field types, the D-R-A<sub>&#x0394;</sub>- &#x0394;-m<sub>00</sub> set provides the highest classification accuracy, followed by the D-R-P<sub>&#x0394;</sub>-&#x0394;-m<sub>00</sub> set which also provides better accuracy than the widely used H -&#x03B1;-(&#x03B4;-&#x03B3;)-A-span set. The proposed method would be valuable for Pol-SAR interpretation.
URI: http://localhost/handle/Hannan/157615
http://localhost/handle/Hannan/627013
ISSN: 1545-598X
1558-0571
volume: 13
issue: 4
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7419830.pdf1.77 MBAdobe PDFThumbnail
Preview File
Title: Pol-SAR Classification Based on Generalized Polar Decomposition of Mueller Matrix
Authors: Hanning Wang;Zhimin Zhou;John Turnbull;Qian Song;Feng Qi
subject: Mueller matrix|Generalized polar decomposition|roll-invariant parameters|polarimetric SAR classification
Year: 2016
Publisher: IEEE
Abstract: In this letter, we investigate an application of a generalized polar decomposition of the Mueller matrix for polarimetric synthetic aperture radar (Pol-SAR) classification. Six roll-invariant parameters (diattenuation, retardance, polarization power, depolarization anisotropy, depolarization power, and transmittance) are selected as features for the classification of scattering types. Experimental results using the AIRSAR data over Flevoland show that, for most field types, the D-R-A<sub>&#x0394;</sub>- &#x0394;-m<sub>00</sub> set provides the highest classification accuracy, followed by the D-R-P<sub>&#x0394;</sub>-&#x0394;-m<sub>00</sub> set which also provides better accuracy than the widely used H -&#x03B1;-(&#x03B4;-&#x03B3;)-A-span set. The proposed method would be valuable for Pol-SAR interpretation.
URI: http://localhost/handle/Hannan/157615
http://localhost/handle/Hannan/627013
ISSN: 1545-598X
1558-0571
volume: 13
issue: 4
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7419830.pdf1.77 MBAdobe PDFThumbnail
Preview File