A Modified Four-Component Decomposition Method With Refined Volume Scattering Models

Wang, Yu; Yu, Weidong; Wang, Chunle; Liu, Xiuqing

doi:10.1109/jstars.2020.2990691

Cited by 7 publications

(6 citation statements)

References 39 publications

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“…Using the refined volume scattering corresponding to [37] and the proposed coupling scattering components, the P5SD and PI5SD can be proposed to evaluate the performance of the new scattering models, and the coherency matrix can be divided into…”

Section: Decomposition Methods Of Polsar and Polinsar Datamentioning

confidence: 99%

“…In this case, the traditional volume scattering models are not suitable for the ground truth. In this article, refined volume scattering models of PolSAR, corresponding to [37], are introduced to characterize the scattering mechanisms of various land covers.…”

Section: A Compound Scattering Matrixmentioning

confidence: 99%

“…(1−PISP) 2 > 0, rr is an incremental function of the PISP, which can be adaptively changed in the volume scattering model. When rr ≤ 1, the scattering mechanism of this region is stochastic, and the volume scattering models are the same as that in [37]. When rr > 1, the scattering mechanism of this region is deterministic, and the modified volume scattering models obtained via (24) are used for the decomposition.…”

Section: B Modification Of Polinsar Volume Scattering Modelsmentioning

confidence: 99%

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Five-Component Decomposition Methods of Polarimetric SAR and Polarimetric SAR Interferometry Using Coupling Scattering Mechanisms

Wang

Hou

2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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In this article, five-component model-based decomposition methods of polarimetric synthetic aperture radar (PolSAR) (P5SD) and polarimetric synthetic aperture radar interferometry (PolInSAR) (PI5SD) using coupling scattering mechanisms are proposed. The target of these methods is to overcome the overestimation of volume scattering and to mitigate the mixed ambiguity of the scattering mechanism. First, coupling scattering models are proposed to decompose the coherency matrix into five submatrices. According to the traditional seven-component decomposition method proposed by Singh et al., the helix and mixed dipole can be merged into a coupling component, while the oriented dipole and compound dipole can also be generated in a general form. Then, the refined volume scattering models of PolSAR are introduced to characterize the volume scattering power of various land covers. The polarimetric interferometric similarity parameter (PISP) is introduced to modify the refined volume scattering models, and it can be used to further reduce the volume scattering contribution of building areas with large orientation angles. In addition, a feature named θ dv , total power, and PISP are embedded in the building area identification, and the building extraction results are used as the branch condition of the volume scattering model selection. In this article, the validity of P5SD and PI5SD can be demonstrated using airborne L-band E-SAR PolInSAR datasets and airborne C-band PolInSAR data collected by the Aerospace Information Research Institute, Chinese Academy of Sciences. The experimental results demonstrate that the P5SD and PI5SD can be used to effectively interpret the scattering characteristics of the ambiguous regions.

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Section: Decomposition Methods Of Polsar and Polinsar Datamentioning

confidence: 99%

Section: A Compound Scattering Matrixmentioning

confidence: 99%

Section: B Modification Of Polinsar Volume Scattering Modelsmentioning

confidence: 99%

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Five-Component Decomposition Methods of Polarimetric SAR and Polarimetric SAR Interferometry Using Coupling Scattering Mechanisms

Wang

Hou

2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…In this paper, different from the traditional decomposition methods, refined volume scattering models are proposed to better characterize the volume scattering elements of the coherency matrix. The mathematical forms of the coherency elements can be derived as [18], [31]:…”

Section: Refined Volume Scattering Modelsmentioning

confidence: 99%

Seven-Component Decomposition Using Refined Volume Scattering Models and New Configurations of Mixed Dipoles

Wang

Liu

et al. 2020

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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In this paper, an extended seven-component decomposition method using refined volume scattering models and new configurations of mixed dipoles (M7SD) is proposed to interpret the scattering mechanisms of various terrain types. In the M7SD, refined volume scattering models are proposed to reasonably characterize the scattering mechanisms of various land covers with different orientation angles, and the redefined configurations of the mixed dipoles, which have better explanations for the scattering mechanisms, are introduced. Although the diameter of the dipole used in the experiment is very small, the superposition of two dipoles in the same plane will cause one of the dipoles to have a distance from the plane. According to the experimental results, since the distance between one of the dipoles and plane cannot be ignored, it will cause an error between the scattering matrix obtained by the experiment and the scattering matrix obtained under ideal conditions. In this case, in the M7SD, two dipoles are placed in two planes, respectively, with a distance of half wavelength. The performance of the proposed method is demonstrated and evaluated with the spaceborne C-band GaoFen-3, Radarsat-2 and airborne Lband ESAR fully polarimetric data over different study sites. The experimental results demonstrate that the use of M7SD can reasonably interpret the scattering mechanisms of various terrain types (especially the building areas with large orientation angles), overcome the overestimation of the volume scattering and reduce the percentage of negative scattering power pixels.

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“…For example, An et al [16] modelled the unitary matrix with the maximum polarization entropy and designed a new model, which shows high volume scattering power over vegetated areas. Wang et al [17] introduced the polarization orientation angle into the probability density function to obtain a novel volume scattering model. Quan et al [18] proposed an OOB descriptor and modified the matrix elements to describe the scattering characteristics of oriented buildings.…”

Section: Introductionmentioning

confidence: 99%

Model-Based Polarimetric Target Decomposition With Power Redistribution for Urban Areas

Hu,

Wang,

Sun

et al. 2023

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Polarimetric decomposition of oriented buildings is challenging due to their variable orientation angles and structures. Both vegetated and oriented built-up areas generate the HV component namely cross-polarized scattering, leading to an overestimation of volume scattering (OVS). It can cause misinterpretation of the scattering mechanisms between oriented built-up and vegetated areas. In this article, we use a pure volume scattering model designed for completely random scattering to describe the scattering of vegetated areas. At the same time, a new urban revised rate is proposed by considering the rotated dihedral model and introducing polarimetric asymmetry (PA), which can distinguish different areas and reduce OVS in urban areas through power transfer strategy. Then a new model-based polarimetric target decomposition with power redistribution for urban areas is proposed. The performance of our proposed method is verified by RADARSAT-2 C-band and UAVSAR Lband data. The results show that our method can not only better characterize the scattering of oriented buildings compared to previous methods, but also maintain the scattering power of natural areas. It can alleviate the scattering misinterpretation problem between oriented built-up and natural areas.

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A Modified Four-Component Decomposition Method With Refined Volume Scattering Models

Cited by 7 publications

References 39 publications

Five-Component Decomposition Methods of Polarimetric SAR and Polarimetric SAR Interferometry Using Coupling Scattering Mechanisms

Five-Component Decomposition Methods of Polarimetric SAR and Polarimetric SAR Interferometry Using Coupling Scattering Mechanisms

Seven-Component Decomposition Using Refined Volume Scattering Models and New Configurations of Mixed Dipoles

Model-Based Polarimetric Target Decomposition With Power Redistribution for Urban Areas

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