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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>Δ</sub>- Δ-m<sub>00</sub> set provides the highest classification accuracy, followed by the D-R-P<sub>Δ</sub>-Δ-m<sub>00</sub> set which also provides better accuracy than the widely used H -α-(δ-γ)-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 | Size | Format | |
---|---|---|---|---|
7419830.pdf | 1.77 MB | Adobe PDF | ![]() 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>Δ</sub>- Δ-m<sub>00</sub> set provides the highest classification accuracy, followed by the D-R-P<sub>Δ</sub>-Δ-m<sub>00</sub> set which also provides better accuracy than the widely used H -α-(δ-γ)-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 | Size | Format | |
---|---|---|---|---|
7419830.pdf | 1.77 MB | Adobe PDF | ![]() 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>Δ</sub>- Δ-m<sub>00</sub> set provides the highest classification accuracy, followed by the D-R-P<sub>Δ</sub>-Δ-m<sub>00</sub> set which also provides better accuracy than the widely used H -α-(δ-γ)-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 | Size | Format | |
---|---|---|---|---|
7419830.pdf | 1.77 MB | Adobe PDF | ![]() Preview File |