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An innovative minimum cost flow phase unwrapping algorithm based on compressive sensing for multi-temporal small baseline DInSAR interferograms sequences.

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Title:	An innovative minimum cost flow phase unwrapping algorithm based on compressive sensing for multi-temporal small baseline DInSAR interferograms sequences.
Authors:	Yasir, Muhammad¹ (AUTHOR), Casu, Francesco² (AUTHOR), Luca, Claudio De¹ (AUTHOR), Onorato, Giovanni¹ (AUTHOR), Lanari, Riccardo¹ (AUTHOR), Manunta, Michele¹ (AUTHOR)
Source:	ISPRS Journal of Photogrammetry & Remote Sensing. Jun2026, Vol. 236, p120-140. 21p.
Subjects:	Phase unwrapping (Digital image processing), Compressed sensing, Synthetic aperture radar, Volcanic activity prediction, Radar interferometry
Geographic Terms:	Italy
Abstract:	We present an innovative Phase Unwrapping (PhU) method for multi-temporal, small baseline differential interferogram sequences that benefits from the Minimum Cost Flow (MCF) algorithm and the Compressive Sensing (CS) theory. The developed algorithm advances the Extended MCF (EMCF) method by (1) introducing a new approach for the temporal PhU operation and (2) enhancing the retrieval capability of the existing spatial PhU procedure. In particular, the temporal PhU exploits the sparsity of the phase gradient signal and efficiently searches for a minimum L 1 -norm solution in the temporal/perpendicular baseline plane with no need, unlike the EMCF method, of any Delaunay triangulation in this domain. Furthermore, the spatial PhU capitalizes on the obtained temporal solution and performs a multi-trial PhU operation of each interferogram by exploiting different cost functions; the final unwrapped interferograms are then obtained through a pixel-by-pixel weighted average of the unwrapped solutions retrieved in each trial. To evaluate the performance of the proposed algorithm, which is tailored to multi-look interferograms, we carry out a comparative analysis with the results of the original EMCF technique by using simulated and real SAR data. In particular, we process a SAOCOM-1 (L-band) SAR dataset acquired over the Stromboli Island, characterized by intense and fast deformation signals, to assess the algorithm effectiveness when dealing with challenging DInSAR interferogram sequences obtained from a limited number of SAR acquisitions. Subsequently, the performance of the proposed PhU approach is further investigated by processing two large Sentinel-1 (C-band) datasets acquired over the Stromboli Island and the Etna Volcano, both sites located in southern Italy. The obtained results clearly show the robustness and effectiveness of the developed technique in retrieving the detected displacement signals, even when characterized by fast and highly nonlinear behaviors. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
Abstract:	We present an innovative Phase Unwrapping (PhU) method for multi-temporal, small baseline differential interferogram sequences that benefits from the Minimum Cost Flow (MCF) algorithm and the Compressive Sensing (CS) theory. The developed algorithm advances the Extended MCF (EMCF) method by (1) introducing a new approach for the temporal PhU operation and (2) enhancing the retrieval capability of the existing spatial PhU procedure. In particular, the temporal PhU exploits the sparsity of the phase gradient signal and efficiently searches for a minimum L 1 -norm solution in the temporal/perpendicular baseline plane with no need, unlike the EMCF method, of any Delaunay triangulation in this domain. Furthermore, the spatial PhU capitalizes on the obtained temporal solution and performs a multi-trial PhU operation of each interferogram by exploiting different cost functions; the final unwrapped interferograms are then obtained through a pixel-by-pixel weighted average of the unwrapped solutions retrieved in each trial. To evaluate the performance of the proposed algorithm, which is tailored to multi-look interferograms, we carry out a comparative analysis with the results of the original EMCF technique by using simulated and real SAR data. In particular, we process a SAOCOM-1 (L-band) SAR dataset acquired over the Stromboli Island, characterized by intense and fast deformation signals, to assess the algorithm effectiveness when dealing with challenging DInSAR interferogram sequences obtained from a limited number of SAR acquisitions. Subsequently, the performance of the proposed PhU approach is further investigated by processing two large Sentinel-1 (C-band) datasets acquired over the Stromboli Island and the Etna Volcano, both sites located in southern Italy. The obtained results clearly show the robustness and effectiveness of the developed technique in retrieving the detected displacement signals, even when characterized by fast and highly nonlinear behaviors. [ABSTRACT FROM AUTHOR]
ISSN:	09242716
DOI:	10.1016/j.isprsjprs.2026.03.040