Wang, Yu ; Yu, Weidong ; Liu, Xiuqing ; Wang, Chunle ; Kuijper, Arjan ; Guthe, Stefan (2020)
Demonstration and Analysis of an Extended Adaptive General Four-Component Decomposition.
In: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 13
doi: 10.1109/JSTARS.2020.2996801
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
The overestimation of volume scattering is an essentialshortcoming of the model-based polarimetric syntheticaperture radar (PolSAR) target decomposition method. It islikely to affect the measurement accuracy and result in mixedambiguity of scattering mechanism. In this paper, an extendedadaptive four-component decomposition method (ExAG4UThs)is proposed. First, the orientation angle compensation (OAC)is applied to the coherency matrix and artificial areas areextracted as the basis for selecting the decomposition method.Second, for the decomposition of artificial areas, one of the twocomplex unitary transformation matrices of the coherency matrixis selected according to the wave anisotropy (Aw). In addition, thebranch condition that is used as a criterion for the hierarchicalimplementation decomposition is the ratio of the correlationcoefficient (Rcc). Finally, the selected unitary transformationmatrix and discriminative threshold are used to determine thestructure of the selected volume scattering models, which aremore effectively to adapt to various scattering mechanisms. Inthis paper, the performance of the proposed method is evaluatedon GaoFen-3 full PolSAR data sets for various time periods andregions. The experimental results demonstrate that the proposedmethod can effectively represent the scattering characteristics ofthe ambiguous regions and the oriented building areas can bewell discriminated as dihedral or odd-bounce structures.
Typ des Eintrags: | Artikel |
---|---|
Erschienen: | 2020 |
Autor(en): | Wang, Yu ; Yu, Weidong ; Liu, Xiuqing ; Wang, Chunle ; Kuijper, Arjan ; Guthe, Stefan |
Art des Eintrags: | Bibliographie |
Titel: | Demonstration and Analysis of an Extended Adaptive General Four-Component Decomposition |
Sprache: | Englisch |
Publikationsjahr: | 28 Mai 2020 |
Verlag: | IEEE |
Titel der Zeitschrift, Zeitung oder Schriftenreihe: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Jahrgang/Volume einer Zeitschrift: | 13 |
DOI: | 10.1109/JSTARS.2020.2996801 |
Kurzbeschreibung (Abstract): | The overestimation of volume scattering is an essentialshortcoming of the model-based polarimetric syntheticaperture radar (PolSAR) target decomposition method. It islikely to affect the measurement accuracy and result in mixedambiguity of scattering mechanism. In this paper, an extendedadaptive four-component decomposition method (ExAG4UThs)is proposed. First, the orientation angle compensation (OAC)is applied to the coherency matrix and artificial areas areextracted as the basis for selecting the decomposition method.Second, for the decomposition of artificial areas, one of the twocomplex unitary transformation matrices of the coherency matrixis selected according to the wave anisotropy (Aw). In addition, thebranch condition that is used as a criterion for the hierarchicalimplementation decomposition is the ratio of the correlationcoefficient (Rcc). Finally, the selected unitary transformationmatrix and discriminative threshold are used to determine thestructure of the selected volume scattering models, which aremore effectively to adapt to various scattering mechanisms. Inthis paper, the performance of the proposed method is evaluatedon GaoFen-3 full PolSAR data sets for various time periods andregions. The experimental results demonstrate that the proposedmethod can effectively represent the scattering characteristics ofthe ambiguous regions and the oriented building areas can bewell discriminated as dihedral or odd-bounce structures. |
Freie Schlagworte: | Light scattering, Imaging technology concepts, Satellite data, Satellite images |
Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Graphisch-Interaktive Systeme 20 Fachbereich Informatik > Mathematisches und angewandtes Visual Computing |
Hinterlegungsdatum: | 19 Okt 2020 08:29 |
Letzte Änderung: | 09 Dez 2021 09:49 |
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