arXiv Open Access 2022

Sparse InSAR Data 3D Inpainting for Ground Deformation Detection Along the Rail Corridor

Odysseas Pappas Juliet Biggs David Bull Alin Achim Nantheera Anantrasirichai

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Abstrak

Monitoring of ground movement close to the rail corridor, such as that associated with landslips caused by ground subsidence and/or uplift, is of great interest for the detection and prevention of possible railway faults. Interferometric synthetic-aperture radar (InSAR) data can be used to measure ground deformation, but its use poses distinct challenges, as the data is highly sparse and can be particularly noisy. Here we present a scheme for processing and interpolating noisy, sparse InSAR data into a dense spatio-temporal stack, helping suppress noise and opening up the possibility for treatment with deep learning and other image processing methods.

Topik & Kata Kunci

eess.IV

Penulis (5)

Odysseas Pappas

Juliet Biggs

David Bull

Alin Achim

Nantheera Anantrasirichai

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APA MLA BibTeX

Pappas, O., Biggs, J., Bull, D., Achim, A., Anantrasirichai, N. (2022). Sparse InSAR Data 3D Inpainting for Ground Deformation Detection Along the Rail Corridor. https://arxiv.org/abs/2203.02407

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Tahun Terbit: 2022
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓