A PolSAR Scattering Power Factorization Framework and Novel Roll-Invariant Parameter-Based Unsupervised Classification Scheme Using a Geodesic Distance
| Autor: | Debanshu Ratha, Avik Bhattacharya, Alejandro C. Frery, Eric Pottier |
|---|---|
| Přispěvatelé: | Indian Institute of Technology Bombay (IIT Bombay), Institut d'Électronique et des Technologies du numéRique (IETR), Nantes Université (NU)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Universidade Federal de Alagoas = Federal University of Alagoas (UFAL), Xidian University, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Fundação de Amparo à Pesquisa do Estado de Alagoas, Université de Nantes (UN)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS), Université de Nantes (UN)-Université de Rennes 1 (UR1) |
| Rok vydání: | 2020 |
| Předmět: |
Standards
010504 meteorology & atmospheric sciences Geodesic 0211 other engineering and technologies 02 engineering and technology Similarity measure 01 natural sciences Matrix decomposition Scattering Matrix (mathematics) Factorization 0103 physical sciences Context modeling Power measurement Electrical and Electronic Engineering Invariant (mathematics) Linear combination 010303 astronomy & astrophysics 0105 earth and related environmental sciences 021101 geological & geomatics engineering Mathematics Radar Mathematical analysis Level measurement [SPI.TRON]Engineering Sciences [physics]/Electronics [SPI.ELEC]Engineering Sciences [physics]/Electromagnetism General Earth and Planetary Sciences [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing |
| Zdroj: | IEEE Transactions on Geoscience and Remote Sensing IEEE Transactions on Geoscience and Remote Sensing, Institute of Electrical and Electronics Engineers, 2020, 58 (5), pp.3509-3525. ⟨10.1109/TGRS.2019.2957514⟩ IEEE Transactions on Geoscience and Remote Sensing, 2020, 58 (5), pp.3509-3525. ⟨10.1109/TGRS.2019.2957514⟩ |
| ISSN: | 1558-0644 0196-2892 |
| Popis: | We propose a generic scattering power factorization framework (SPFF) for polarimetric synthetic aperture radar (PolSAR) data to directly obtain $N$ scattering power components along with a residue power component for each pixel. Each scattering power component is factorized into similarity (or dissimilarity) using elementary targets and a generalized volume model. The similarity measure is derived using a geodesic distance between pairs of $4\times 4$ real Kennaugh matrices. In standard model-based decomposition schemes, the $3\times 3$ Hermitian-positive semi-definite covariance (or coherency) matrix is expressed as a weighted linear combination of scattering targets following a fixed hierarchical process. In contrast, under the proposed framework, a convex splitting of unity is performed to obtain the weights while preserving the dominance of the scattering components. The product of the total power (Span) with these weights provides the nonnegative scattering power components. Furthermore, the framework, along with the geodesic distance ( ${GD}$ ) is effectively used to obtain specific roll-invariant parameters such as scattering-type parameter ( $\alpha _{GD}$ ), helicity parameter ( $\tau _{GD}$ ), and purity parameter ( $P_{GD}$ ). A $P_{GD}/\alpha _{GD}$ unsupervised classification scheme is also proposed for PolSAR images. The SPFF, the roll invariant parameters, and the classification results are assessed using C-band RADARSAT-2 and L-band ALOS-2 images of San Francisco. |
| Databáze: | OpenAIRE |
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