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Refined 3D Urban Building Reconstruction from TomoSAR Point Clouds via Multi-Level Geometric Priors and Shadow

Wenkang Liu¹, Haoyuan Chen², Jinsong Zhang¹

¹The School of Information Mechanics and Sensing Engineering, Xidian University, Xi'an 710071, China.

Sensors (Basel, Switzerland)

|July 15, 2026

Summary

This study refines urban building modeling from TomoSAR point clouds by integrating structural priors and novel algorithms for improved accuracy and detail. The method enhances geometric fidelity in urban reconstructions, overcoming limitations of current techniques.

Keywords:

3D model reconstruction SAR tomography (TomoSAR)point cloud regularization

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Correlative Microscopy for 3D Structural Analysis of Dynamic Interactions

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Published on: June 24, 2013

Area of Science:

Geoinformatics
Remote Sensing
Computer Vision

Background:

Urban building modeling from TomoSAR point clouds faces challenges like limited resolution, low elevation accuracy, and data artifacts.
These issues hinder the extraction of detailed and accurate 3D building models.

Purpose of the Study:

To propose a refined urban building modeling method using structural priors (directionality, orthogonality, symmetry).
To enhance the accuracy and geometric fidelity of building models reconstructed from TomoSAR data.

Main Methods:

Piecewise fitting with density-based segmentation for estimating building directions and complex façade geometry.
Adaptive Douglas-Peucker algorithm with symmetry evaluation for roof extraction and defect repair.
Building shadow analysis for estimating building width in cases of missing roof data.

Main Results:

The proposed method significantly improves reconstruction accuracy and geometric fidelity in urban areas.
Demonstrated superior performance compared to existing state-of-the-art approaches on benchmark datasets (SARMV3D-1.0, SARMV3D-3.0).

Conclusions:

The integration of structural priors and novel algorithms effectively addresses limitations in TomoSAR-based building modeling.
This approach enables more detailed and accurate 3D urban building reconstructions from point cloud data.