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A Probabilistic-Cost Algorithm for Large-Scale 2D Phase Unwrapping — arXiv:2609.36267

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.36267
License (as archived): CC0-1.0
Archived: 2026-10-07T20:52:04.621Z
SHA-256 of the archived text: 02e025cc4eb032acc44af2f66bc2a2f0e995ff06aad5eaef8291ad840e05bd44
Stable URL of this page: https://metraipolis.com/documento/dc_00a7d0229108

How to cite

A Probabilistic-Cost Algorithm for Large-Scale 2D Phase Unwrapping — arXiv:2609.36267 — arXiv (en), https://arxiv.org/abs/2609.36267 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_00a7d0229108 (Metraipolis archive dc_00a7d0229108, sha256 02e025cc4eb032acc44af2f66bc2a2f0e995ff06aad5eaef8291ad840e05bd44)

BibTeX

@misc{dc00a7d0229108,
  title = {A Probabilistic-Cost Algorithm for Large-Scale 2D Phase Unwrapping — arXiv:2609.36267},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.36267},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_00a7d0229108; sha256 02e025cc4eb032acc44af2f66bc2a2f0e995ff06aad5eaef8291ad840e05bd44},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.36267. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Two-dimensional phase unwrapping can dominate computation and memory usage in wide-area Interferometric Synthetic Aperture Radar (InSAR) processing. Here we present Whirlwind, a minimum-cost-flow (MCF) unwrapper tailored for large interferograms of surface deformation. We derive fixed likelihood-ratio costs using multilook interferometric phase statistics, marginalizing uncertainty in the local phase-gradient and coherence estimates. A compact integer lookup table and parallel-augmenting successive-shortest-path solver with Dial bucket queues make the MCF solve efficient while avoiding flow-dependent cost relinearization. We test whether these improvements in speed and memory can be obtained without a loss of solution quality using multiple evaluation criteria for individual interferograms, at mission-production scale, and in end-to-end displacement time series solutions. On a 74-Mpixel Sentinel-1 interferogram of the 2019 Ridgecrest earthquakes, Whirlwind runs in 209 s, 28x faster than single-tile SNAPHU, while using 40% of the peak memory. Across 6,014 provisional NISAR geocoded unwrapped (GUNW) products, 93% agreed with the SNAPHU-derived results on more than 99% of valid pixels; on seven challenging 77-MHz Antarctic frames, Whirlwind ran a median 21x faster than SNAPHU while matching 99.4% of its integer-cycle assignments. Finally, in a complete Sentinel-1 time series experiment, Whirlwind improved the network-inversion consistency over SNAPHU, and in a high-resolution Capella time series of the Portuguese Bend landslide, it achieved the highest correlation with a dense GPS network among five unwrapping configurations. Whirlwind is provided as an open-source library capable of handling the growing volume of globally available InSAR data.

Tema degli esploratori: statistica e scienza dei dati (retro-catalogo arXiv: annunci del 2026-09-30 in eess.SP).
Categorie arXiv: Signal Processing (eess.SP).
Pagina del lavoro: https://arxiv.org/abs/2609.36267 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-07T20:14:59.970Z dalla pagina https://arxiv.org/catchup/eess.SP/2026-09-30?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).