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Mathematics, Electrical Engineering, Electronic engineering, Information engineering, Earth and Related Environmental Sciences
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Modifying the Yamaguchi FourComponent Decomposition Scattering Powers Using a Stochastic Distance
Modelbased decompositions have gained considerable attention after the initial work of Freeman and Durden. This decomposition, which assumes the target to be reflectionsymmetric, was later relaxed in the Yamaguchi <italic>et al.</italic> decomposition with the addition of the helix parameter. Since then, many decomposition have been proposed where either the scattering model was modified to fit the data or the coherency matrix representing the secondorder statistics of the full polarimetric data is rotated to fit the scattering model. In this paper, we propose to modify the Yamaguchi fourcomponent decomposition (Y4O) scattering powers using the concept of statistical information theory for matrices. In order to achieve this modification, we propose a method to estimate the polarization orientation angle (OA) from fullpolarimetric SAR images using the Hellinger distance. In this method, the OA is estimated by maximizing the Hellinger distance between the unrotated and the rotated <inlineformula><texmath notation="LaTeX">$\mathbf{T}_{33}$</texmath></inlineformula> and the <inlineformula><texmath notation="LaTeX">$\mathbf{T}_{22}$</texmath></inlineformula> components of the coherency matrix <inlineformula><texmath notation="LaTeX">$\mathbf{[T]}$</texmath></inlineformula>. Then, the powers of the Yamaguchi fourcomponent modelbased decomposition (Y4O) are modified using the maximum relative stochastic distance between the <inlineformula><texmath notation="LaTeX">$\mathbf{T}_{33}$</texmath></inlineformula> and the <inlineformula><texmath notation="LaTeX">$\mathbf{T}_{22}$</texmath></inlineformula> components of the coherency matrix at the estimated OA. The results show that the overall doublebounce powers over rotated urban areas have significantly improved with the reduction of volume powers. The percentage of pixels with negative powers have also decreased from the Y4O decomposition. The proposed method is both qualitatively and quantitatively compared with the results obtained from the Y4O and the Y4R decompositions for a Radarsat2 Cband SanFrancisco dataset and an UAVSAR Lband Hayward dataset. 
An Adaptive General FourComponent Scattering Power Decomposition With Unitary Transformation of Coherency Matrix (AG4U)
An adaptive general fourcomponent scattering power decomposition method (AG4U) is proposed in this letter. The degree of polarization <inlineformula> <texmath notation="LaTeX">$m$</texmath></inlineformula> is used as a criterion for the adaptive nature of the proposed decomposition. In this method, one among the two complex special unitary transformation matrices is chosen to transform a real unitary rotated coherency matrix based on the largest value of <inlineformula> <texmath notation="LaTeX">$m$</texmath></inlineformula>. This transformed matrix is then utilized for the existing Yamaguchi <italic>et al.</italic> fourcomponent decomposition scheme with an extended volume scattering model. The proposed decomposition is applied to Radarsat2 fullpolarimetic Cband data over San Francisco and Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) fullpolarimetric Lband data over the Hayward Fault in California. The scattering powers estimated from the decomposition techniques of Yamaguchi <italic>et al.</italic> (Y4O), Singh <italic>et al.</italic> (G4U) , and AG4U are compared. AG4U shows appreciable improvements in the scattering powers, particularly in urban areas oriented about the radar line of sight compared with the Y4O and G4U decompositions. It also shows reduced percentage of pixels with negative powers considerably compared with the Y4O decomposition. 
Bhattacharya, A., De, S., Muhuri, A., Surendar, M., Venkataraman, G., & Das, A. K. (2015). A new compact polarimetric SAR decomposition technique. Remote Sensing Letters, 6(12), 914923.