Geometric constraints based 3D reconstruction method of tomographic SAR for buildings

Han, Dong; Zhang, Jiao; Zhou, Liangjiang; Ding, Chibiao; Wu, Yirong

doi:10.1007/s11432-022-3521-0

Cited by 8 publications

(5 citation statements)

References 30 publications

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“…To exhibit the details in Z-structure prior information extraction, the proposed SAR tomography method is first applied to single buildings in Yuncheng and Emeishan. Results are evaluated by three indicators, including discrete ratio (DR) [16], TomoSAR point cloud entropy (3D entropy) [16], and the average neighborhood height difference Afterwards, the Z-structure information of entire areas is extracted in the experiments. The Z-FISTA algorithm, which achieves the best 3D reconstruction results on single building targets, is utilized for reconstruction of entire urban scene.…”

Section: Experimental Results and Analysismentioning

confidence: 99%

“…3) The proposed method outperforms traditional method without Z-structure constraint in point cloud concentration and accuracy [14,16], which can better reconstruct the building faç ades and preserve the geometrical structure of different floors. The rest of this paper is organized as follows.…”

Section: Introductionmentioning

confidence: 92%

“…Lei et al proposed a joint sparse imaging algorithm based on constructing interest points and maximum likelihood estimation, which reduces the number of acquisitions of TomoSAR observations and suppresses scatterer outliers [15]. Dong et al proposed an algorithm that applies the extracted building faç ade geometry and the SNR of SAR images as prior information into an adaptive iterative shrinkage threshold algorithm, which successfully improves the single building reconstruction [16].…”

Section: Introductionmentioning

confidence: 99%

“…the components of scatterers in the pixel and the Z-structure constraints marked in origin are shown in Fig.8.This paper introduces the SNR index[16] to set a relaxation value for the Z-structure constraint. Given a sparse range…”

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confidence: 99%

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Urban SAR Tomography With Z-Structure Constraint of Buildings

Guo,

Gao,

Ren

et al. 2024

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

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Synthetic aperture radar (SAR) tomography (TomoSAR) technology effectively mitigates issues like severe layover in high-resolution SAR urban imagery, presenting numerous applications in reconstructing complex threedimensional (3D) urban scenes. However, prevailing TomoSAR methodologies usually overlook the geometrical feature of the targets, which are particularly pronounced in buildings in urban scenes. To improve the quality of 3D reconstruction of building targets for large-scale urban scenes, we propose a geometric guided SAR tomography processing in this paper. Firstly, the geometrical feature referred to Z-structure of buildings in TomoSAR point cloud is studied. Then, a Z-structure information extraction approach is proposed to provide prior information for subsequent geometric constraints. Finally, the Zstructure constraint based tomographic algorithm is proposed, optimizing the solution space of the original algorithms. Experiments are conducted on real SAR data and 3D point clouds of the entire urban scenes is obtained. The proposed algorithm demonstrates commendable performance in point cloud entropy and concentration, especially in the inversion of different floor structures.

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Section: Experimental Results and Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Urban SAR Tomography With Z-Structure Constraint of Buildings

Guo,

Gao,

Ren

et al. 2024

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

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show abstract

“…Synthetic aperture radar tomography (TomoSAR) can reconstruct high-resolution 3D structures of targets from a stack of coregistered SAR images and has the advantage of being unaffected by weather conditions, time, and terrain limitations. Recently, it has been applied to city modeling, geological exploration, environmental monitoring, target detection, military reconnaissance, and other fields [1][2][3][4].…”

Section: Introductionmentioning

confidence: 99%

Exploiting SAR visual semantics in TomoSAR for 3D modeling of buildings

Wang,

et al. 2024

NSO

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Recently a new paradigm is emerging in SAR (Synthetic Aperture Radar) 3D imaging technology where the imaging performance is enhanced by exploiting SAR visual semantics. Here by "SAR visual semantics", we mean primarily the scene conceptual structural information extracted directly from SAR images. Under this paradigm, a paramount open problem lies in what and how the SAR visual semantics could be extracted and used at different levels associated with different structural information. This work is a tentative attempt to tackle the above what-and-how problem, and it mainly consists of the following two parts: The first one is a sketchy description of how three-level (low, middle, and high) SAR visual semantics could be extracted and used in SAR Tomography (TomoSAR), including an extension of SAR visual semantics analysis (e.g., faç ades and roofs) to sparse 3D points initially recovered via traditional TomoSAR methods. The second part is a case of study on two open source TomoSAR datasets to illustrate and validate the effectiveness and efficiency of SAR visual semantics exploitation in TomoSAR for box-like 3D building modeling. Due to the space limit, only main steps of the involved methods are reported, and we hope, such neglects of technical details will not severely compromise the underlying key concepts and ideas.

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