Scattering Characterization of Obliquely Oriented Buildings from PolSAR Data Using Eigenvalue-Related Model

Quan, Sinong; Xiong, Boli; Xiang, Deliang; Hu, Canbin; Kuang, Gangyao

doi:10.3390/rs11050581

Cited by 13 publications

(30 citation statements)

References 24 publications

(60 reference statements)

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“…To separate the cross-pol components caused by oriented dihedrals from the overall cross-pol components, Xiang et al proposed the well-known cross scattering model, which is formed from a rotated dihedral structure considering its orientation angle [22]. However, there exist some intrinsic drawbacks in the CSM in that it includes an approximately equal amount of co-pol component (the T 22 term) and cross-pol component (the T 33 term) according to its algebraic model [22,29]. Meanwhile, in the actual OOB regions, it is observed that cross-pol power is more intense than co-pol power [24][25][26][27][28].…”

Section: Ood Scattering Modelmentioning

confidence: 99%

“…This can also be referred to the color of the bridge, as pointed out by the red arrows. To quantify the results, a high-rise OOB region, which tilted by about 37° from the flight trajectory [29] (outlined by the red rectangle), was selected, and the corresponding normalized scattering power statistics are shown in Table 3. To quantify the results, a high-rise OOB region, which tilted by about 37 • from the flight trajectory [29] (outlined by the red rectangle), was selected, and the corresponding normalized scattering power statistics are shown in Table 3.…”

Section: Further Validation On C-band Datamentioning

confidence: 99%

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Seven-Component Model-Based Decomposition for PolSAR Data with Sophisticated Scattering Models

et al. 2019

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Due to incomprehensive and inaccurate scattering modeling, the state-of-the-art polarimetric synthetic aperture radar (PolSAR) model-based target decompositions are incapable of effectively depicting the scattering mechanism of obliquely oriented urban areas. In this paper, a seven-component model-based decomposition scheme is proposed by constructing several sophisticated scattering models. First, an eigenvalue-based obliquely-oriented dihedral scattering model is presented to reasonably distribute the co-polarization and cross-polarization scattering powers in obliquely oriented urban areas, thus accurately characterizing the urban scattering. Second, the ±45° oriented dipole and ±45° quarter-wave reflector scattering models are incorporated for the purpose of accounting for the real and imaginary components of the T 13 element in the coherency matrix so as to fully utilize polarimetric information. Finally, according to their mathematical forms, several strategies for model parameter solutions are designed, and the seven-component decomposition is fulfilled. Experimental results conducted on different PolSAR data demonstrate that the proposed method considerably improves the PolSAR scattering interpretation in a more physical manner compared to other existing model-based decomposition, which can be applied for urban area detection, classification, and other urban planning applications.

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Section: Ood Scattering Modelmentioning

confidence: 99%

Section: Further Validation On C-band Datamentioning

confidence: 99%

Seven-Component Model-Based Decomposition for PolSAR Data with Sophisticated Scattering Models

et al. 2019

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“…Recently, an OOB scattering model along with an R5CD scheme was proposed, which can effectively characterize building scattering by reducing the volume scattering and enhancing the OOB scattering simultaneously. Considering this, this section briefly reviews the R5CD [24] and presents an R5CD-based building extraction method which detects the AABs and OOBs, respectively. Subject to the reciprocity condition, the acquired coherency matrix can be presented as:…”

Section: Refined Model-based Building Extractionmentioning

confidence: 99%

“…The model can effectively elevate the scattering characteristics of OOBs. According to [24], the OOB scattering matrix is given as…”

Section: Refined Model-based Building Extractionmentioning

confidence: 99%

“…To address these problems, this paper proposes a building extraction method with refined model-based decomposition and robust scattering feature for PolSAR images. First, the scattering powers derived from the refined five component decomposition (R5CD) [24] are integrated. The R5CD is our newly proposed work, which can characterize building scattering by significantly improving the OVS.…”

Section: Introductionmentioning

confidence: 99%

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Refined Model-Based and Feature-Driven Extraction of Buildings from PolSAR Images

et al. 2019

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Polarimetric synthetic aperture radar (PolSAR) building extraction plays an important role in urban planning, disaster management, etc. In this paper, a building extraction method using refined model-based decomposition and robust scattering feature is proposed. On the one hand, the newly proposed refined five-component decomposition and its derived scattering powers are applied to detect the buildings. On the other hand, by combining the matrix elements and co-polarization correlation coefficient, a robust feature is proposed to discriminate buildings and non-buildings. Both these two preliminary extraction results are obtained through thresholding segmentation. Finally, they are fused via the HX Markov random fields so as to further improve the extraction accuracy. The performance of the proposed method is demonstrated and evaluated with Gaofen-3 and uninhabited aerial vehicle SAR full PolSAR data over different test sites. Outputs show that the proposed method outperforms other state-of-the-art methods and provides an overall accuracy of over 90%.

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Scattering Modeling of Urban Oriented Buildings in PolSAR images by Using Adaptive Statistical Distribution

2019

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The cross-polarized scattering (HV) of polarimetric synthetic aperture radar (PolSAR) data is caused not only by forest but also by urban buildings with azimuth orientation angles. Since the general double scattering in model-based decomposition does not support their dominant scattering mechanism, it's still a challenge for modeling the scattering mechanism of oriented buildings. In this paper, the HV induced by oriented buildings is modeled by a rotated dihedral corner reflector. The cross scattering matrix of oriented building is obtained by averaging a cosine squared distribution with its peak at the dominant polarimetric orientation angle (DPOA) of an area and an adaptive width. The relation between DPOA and distribution width is acquired. Then an optimization strategy which eliminates the negative power and balances time and efficiency is proposed to estimate the scattering contributions. The proposed algorithm is tested on AIRSAR data of San Francisco and UAVSAR of San Diego and the results confirm the effectiveness.

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Scattering Characterization of Obliquely Oriented Buildings from PolSAR Data Using Eigenvalue-Related Model

Cited by 13 publications

References 24 publications

Seven-Component Model-Based Decomposition for PolSAR Data with Sophisticated Scattering Models

Seven-Component Model-Based Decomposition for PolSAR Data with Sophisticated Scattering Models

Refined Model-Based and Feature-Driven Extraction of Buildings from PolSAR Images

Scattering Modeling of Urban Oriented Buildings in PolSAR images by Using Adaptive Statistical Distribution

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