View in EDS HTML Full Text PDF Full Text

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

Saved in:
Bibliographic Details
Title: Phase Unwrapping in Seconds: A Spectral ADMM Algorithm for Large-Scale InSAR.
Authors: Rouet-Leduc, Bertrand1 (AUTHOR) rouetleduc.bertrand.5s@kyoto-u.ac.jp, Hulbert, Claudia2 (AUTHOR)
Source: Remote Sensing. Jun2026, Vol. 18 Issue 11, p1801. 17p.
Subjects: Phase unwrapping (Digital image processing), Radar interferometry, Optimization algorithms, Time series analysis, Convex programming, Synthetic aperture radar
Abstract: Highlights: What are the main findings? Phase unwrapping, one of the slowest steps in satellite radar interferometry, can be reformulated as a convex optimization problem that decomposes into trivially parallel operations on GPU. The resulting algorithm, FAUST-ADMM, matches the accuracy of established methods while being up to two orders of magnitude faster, reducing processing times from tens of minutes or even hours to seconds. What are the implications of the main findings? Phase unwrapping is no longer a computational bottleneck in InSAR processing: entire multi-year, multi-track SAR archives can now be routinely unwrapped on a single machine in hours instead of days. This enables exhaustive, automated InSAR time-series analysis at continental to global scales, supporting systematic monitoring of tectonic, volcanic, and anthropogenic ground deformation. Phase unwrapping, the recovery of a continuous signal from measurements known only modulo 2 π , 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 L 1 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. [ABSTRACT FROM AUTHOR]
Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: egs
DbLabel: Engineering Source
An: 194587022
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: Phase Unwrapping in Seconds: A Spectral ADMM Algorithm for Large-Scale InSAR.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Rouet-Leduc%2C+Bertrand%22">Rouet-Leduc, Bertrand</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> rouetleduc.bertrand.5s@kyoto-u.ac.jp</i><br /><searchLink fieldCode="AR" term="%22Hulbert%2C+Claudia%22">Hulbert, Claudia</searchLink><relatesTo>2</relatesTo> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. Jun2026, Vol. 18 Issue 11, p1801. 17p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Phase+unwrapping+%28Digital+image+processing%29%22">Phase unwrapping (Digital image processing)</searchLink><br /><searchLink fieldCode="DE" term="%22Radar+interferometry%22">Radar interferometry</searchLink><br /><searchLink fieldCode="DE" term="%22Optimization+algorithms%22">Optimization algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Time+series+analysis%22">Time series analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Convex+programming%22">Convex programming</searchLink><br /><searchLink fieldCode="DE" term="%22Synthetic+aperture+radar%22">Synthetic aperture radar</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: Highlights: What are the main findings? Phase unwrapping, one of the slowest steps in satellite radar interferometry, can be reformulated as a convex optimization problem that decomposes into trivially parallel operations on GPU. The resulting algorithm, FAUST-ADMM, matches the accuracy of established methods while being up to two orders of magnitude faster, reducing processing times from tens of minutes or even hours to seconds. What are the implications of the main findings? Phase unwrapping is no longer a computational bottleneck in InSAR processing: entire multi-year, multi-track SAR archives can now be routinely unwrapped on a single machine in hours instead of days. This enables exhaustive, automated InSAR time-series analysis at continental to global scales, supporting systematic monitoring of tectonic, volcanic, and anthropogenic ground deformation. Phase unwrapping, the recovery of a continuous signal from measurements known only modulo 2 π , 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 L 1 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. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=194587022
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.3390/rs18111801
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 17
        StartPage: 1801
    Subjects:
      – SubjectFull: Phase unwrapping (Digital image processing)
        Type: general
      – SubjectFull: Radar interferometry
        Type: general
      – SubjectFull: Optimization algorithms
        Type: general
      – SubjectFull: Time series analysis
        Type: general
      – SubjectFull: Convex programming
        Type: general
      – SubjectFull: Synthetic aperture radar
        Type: general
    Titles:
      – TitleFull: Phase Unwrapping in Seconds: A Spectral ADMM Algorithm for Large-Scale InSAR.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Rouet-Leduc, Bertrand
      – PersonEntity:
          Name:
            NameFull: Hulbert, Claudia
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 06
              Text: Jun2026
              Type: published
              Y: 2026
          Identifiers:
            – Type: issn-print
              Value: 20724292
          Numbering:
            – Type: volume
              Value: 18
            – Type: issue
              Value: 11
          Titles:
            – TitleFull: Remote Sensing
              Type: main
ResultId 1