Acta Geodaetica et Cartographica Sinica ›› 2024, Vol. 53 ›› Issue (4): 644-652.doi: 10.11947/j.AGCS.2024.20220633

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The improved max-flow/min-cut weight algorithm for InSAR phase unwrapping

Yandong GAO1,2(), Yikun JIA1,2(), Shijin LI1,2, Yu CHEN1,2, Huaizhan LI1,2, Nanshan ZHENG1,2, Shubi ZHANG1,2   

  1. 1.Key Laboratory of Land Environment and Disaster Monitoring of Natural Resources, China University of Mining and Technology, Xuzhou 221116, China
    2.School of Environment and Spatial Informatics, China University of Mining and Technology, Xuzhou 221116, China
  • Received:2022-11-07 Revised:2023-07-31 Published:2024-05-13
  • Contact: Yikun JIA E-mail:ydgao@cumt.edu.cn;ykjia@cumt.edu.cn
  • About author:GAO Yandong (1988—), male, PhD, associate professor, majors in single/multi-baseline phase unwrapping and InSAR high-precision DEM inversion. E-mail: ydgao@cumt.edu.cn
  • Supported by:
    The National Natural Science Foundation of China(42001409)

Abstract:

InSAR has been widely used in high-precision DEM inversion. The accuracy of phase unwrapping is one of the key steps affecting the accuracy of DEM acquisition, however, the areas with large-gradient changes has been the core issue affecting the accuracy of the unwrapping results. To address this issue, a phase unwrapping max-flow/min-cut algorithm (PUMA) based on the improved weights of the potential function is proposed in this paper. Firstly, the problem of unreasonable weight setting of the PUMA model is studied, and the priori information of the phase gradient change is obtained by using the external existing DEM, and the window maximum absolute phase gradient values are substituted into the corresponding potential function equation to obtain the weight value. Then, through the threshold adjustment of the potential function weight setting, the problem of unwrapping errors caused by the inability of PUMA potential function to function due to unreasonable potential function weight setting is solved, and thus the phase unwrapping accuracy in the region of large gradient change is improved. Finally, the proposed method is validated by simulated data and real TanDEM-X InSAR data, and compared with existing phase unwrapping methods. The results show that the proposed algorithm can improve the deconvolution accuracy by at least 44.93% in the simulated data, and the proposed algorithm can obtain a larger range of effective unwrapping results than the existing algorithm in the region of large gradient variations in the real data.

Key words: InSAR, potential function, max-flow/min-cut, phase unwrapping

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