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https://www.um.edu.mt/library/oar/handle/123456789/104913| Title: | Interferometric phase denoising and unwrapping: a literature review |
| Authors: | Valentino, Gianluca Briffa, Johann Farrugia, Reuben A. Fejjari, Asma |
| Keywords: | Interferometry Synthetic aperture radar Deep learning (Machine learning) |
| Issue Date: | 2023 |
| Publisher: | Malta Chamber of Scientists |
| Citation: | Valentino, G., Briffa, J., Farrugia, R., & Fejjari, A. (2023). Interferometric phase denoising and unwrapping : a literature review. Xjenza Online, 11(Special issue), 49-58. |
| Abstract: | Interferometric SAR (InSAR) phase denoising and phase unwrapping are two key steps of the InSAR pipeline, leading to estimated deformation maps. The objective of this paper is to provide an overview of the recent literature in the field of InSAR phase denoising and unwrapping, and identify the most promising techniques, as well as benchmarks for performance comparison. Summaries of the performance metrics of the various methods are also provided. An example use case of InSAR techniques, including phase denoising and unwrapping, to estimate deformation following a volcanic eruption is provided. |
| URI: | https://www.um.edu.mt/library/oar/handle/123456789/104913 |
| Appears in Collections: | Scholarly Works - FacICTCCE Xjenza, 2023, Volume 11, Special Issue: Top Scientists Xjenza, 2023, Volume 11, Special Issue: Top Scientists |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Interferometric_phase_denoising_and_unwrapping_2023.pdf | 3 MB | Adobe PDF | View/Open |
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