Abstract
This paper improves van Zyl’s Nonnegative Eigenvalue Decomposition (NNED). Orientation angle compensation and helix scattering are introduced to the decomposition. The volume scattering parameters that explain the most cross-polarized power are selected. If volume scattering and helix scattering explain all cross-polarized power in the measured coherency matrix, then simply perform van Zyl decomposition to the remainder matrix; otherwise, the measured coherency matrix is decomposed into three components, i.e., helix scattering, volume scattering, and one ground scattering. The latter two scattering are all modeled by Neumann’s adaptive depolarizing model, according to which some cross-polarized power is attributed to ground scattering hence the orientation angle randomness of volume scattering and the dominant ground scattering are obtained. In this way, all cross-polarized power could be well explained. Experiments using UAVSAR data showed that more than 99.8% of total pixels are well fitted. Negative power is avoided. Compared with van Zyl decomposition, volume scattering power is reduced by up to 8.73% on average. The given volume scattering power is often lower than that by three latest NNED.
Highlights
In the field of polarimetric Synthetic Aperture Radar (PolSAR), model-based incoherent decomposition is an important research topic [1]
Model-based decomposition has been successfully used in PolSAR image classification [17,18,19,20,21], speckle filtering [22], polarimetric SAR Interferometry [23], wetland research [24], soil moisture and roughness estimation [25,26,27], target detection [28,29], disaster assessment [30], and so on
The main differences between the proposed method and van Zyl, Cui, Wang’s Nonnegative Eigenvalue Decompositions (NNED) include: (1) helix scattering are introduced in our method; (2) our method use minimum criterion while the three NNED use maximum criterion; (3) sometimes the dominant ground scattering is described by incoherent and depolarizing models, so there is no remainder component
Summary
In the field of polarimetric Synthetic Aperture Radar (PolSAR), model-based incoherent decomposition is an important research topic [1]. Van Zyl et al [7] demonstrated that if model-based decomposition is valid, after subtracting any components from the observed covariance or coherency matrix, the remainder matrix must be positive semidefinite, or its eigenvalues must be nonnegative. Assumption (RSA) and employment of elemental scatterers of which cross-polarized complex scattering coefficient, or is zero, the derived coherent models of surface scattering and double-bounce scattering cannot describe depolarizing effect It was observed [7] that if volume scattering power is computed with RSA, in many natural forest pixels, volume scattering and helix scattering cannot explain all cross-polarized power.
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