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June 4, 2026Remote Sensing0 citationsOpen Access

Phase Unwrapping in Seconds: A Spectral ADMM Algorithm for Large-Scale InSAR

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BRBertrand Rouet‐LeducCHClaudia Hulbert

Key Points

  • The aim is to develop a fast and accurate algorithm for phase unwrapping in InSAR, making it efficient for large images.
  • Developed FAUST-ADMM, which employs a weighted L1 optimization framework.
  • Used GPU for computation, optimizing each iteration with the Alternating Direction Method of Multipliers.
  • Evaluated on 500 synthetic earthquake interferograms for accuracy and performance.
  • FAUST-ADMM achieved 99% accuracy, matching competing methods and running 10 to 100 times faster.
  • In a real case of a Sentinel-1 dataset, it processed a 6500 × 8500 pixel image in 35 seconds with 99.7% pixel agreement with SNAPHU.
  • Demonstrated practical batch unwrapping of large InSAR time series on a single consumer GPU.

Abstract

Phase unwrapping, the recovery of a continuous signal from measurements known only modulo 2π, is a ubiquitous problem in coherent imaging, from medical MRI to radar remote sensing. In Interferometric Synthetic Aperture Radar (InSAR), phase unwrapping is both critical and computationally demanding: current methods require minutes to hours per interferogram and frequently fail on large images. We present FAUST-ADMM (Fast ADMM Unwrapping via Spectral Transforms), an algorithm that formulates phase unwrapping as a weighted L1 optimization and solves it efficiently on GPU using the Alternating Direction Method of Multipliers (ADMM). Each iteration reduces to a Poisson equation solved in closed form via the Discrete Cosine Transform, followed by element-wise soft thresholding, both trivially parallel. On 500 synthetic earthquake interferograms, FAUST-ADMM achieves 99% accuracy with reference-point correction, matching SNAPHU, MCF, and PUMA, while running 10 to 100× faster. On a full three-subswath Sentinel-1 interferogram of the 2019 Ridgecrest M7.1 earthquake (∼6500 × 8500 pixels), FAUST-ADMM agrees with SNAPHU on 99.7% of pixels in 35 s, a 74× speedup. Our method makes batch unwrapping of large InSAR time series practical on a single consumer GPU.

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Cite This Study

Rouet‐Leduc et al. (2026) studied this question.

synapsesocial.com/papers/6a2117bfd499ed480b1709f1https://doi.org/10.3390/rs18111801
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