Two-dimensional phase unwrapping method using a refined D-LinkNet-based unscented Kalman filter

Gao, Yandong; Wang, Guanghui; Wang, Geng; Li, Tao; Zhang, Shubi; Li, Shijin; Zhang, Yansuo; Zhang, Tao

doi:10.1016/j.optlaseng.2022.106948

Cited by 12 publications

(8 citation statements)

References 37 publications

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“…The proposed CDIF unwrapping process has improved accuracy and efficiency compared to the UIF. The CDIFPU approach can address the unwrapping bias of conventional UKFPU and UIFPU in some local large gradient terrain regions, which is also a continuation of our previous study [15]. Based on the longbaseline interferometric dataset, we have demonstrated the effectiveness of the phase cost indicator and the CDIF unwrapping process.…”

Section: ⅴ Discussionsupporting

confidence: 53%

“…Additionally, we have especially tested the PU performance of the state-of-the-art PUMA based on the interferogram, as shown in Table Ⅱ. It is worth mentioning that in our previous research [15], the PU accuracy of the PGNet method based on this data is 9.5272 rad, and the PU accuracy of the UKFPU based on D-LinkNet is 3.4857 rad, both of which are significantly lower than that of the CDIFPU approach. The unwrapped phase and PU error map of these representative approaches are shown in Fig.…”

Section: A Long-baseline Interferometric Datasetmentioning

confidence: 92%

“…Intriguingly, our recent study demonstrates that the QGPU method can circumvent instead of directly crossing the phase discontinuity region by establishing an appropriate unwrapping path [15]. It implies that the QGPU algorithm has the power to be not entirely forced by the phase continuity assumption by changing the integration order, which makes it possible for traditional single-baseline PU methods to avoid unwrapping error transmission in large gradient regions.…”

Section: Introductionmentioning

confidence: 94%

“…The long-baseline and large-area interferometric datasets are used to test the performance of the phase cost indicatorguided CDIFPU approach proposed in this paper. The PU results are compared and analyzed against other methods, including L 1 -norm [34], minimum-cost flow algorithm (MCF) [27], statistical-cost network-flow algorithm (SNAPHU) [35], UKFPU, UIFPU, PU max-flow/min-cut (PUMA) [36], PGNet, refined D-LinkNet UKFPU [15] and Adaptive Square-Root UKFPU (ASRUKFPU), which was proposed in our previous paper [37]. The accuracy of the PU is mainly assessed through the root-mean-square error (RMSE) between the unwrapped phase and the reference unwrapped phase.…”

Section: Performance Analysismentioning

confidence: 99%

“…It is clear that the fringes of the interferogram are extremely dense. Consequently, this region has become a representative of the performance assessment of single-and multi-baseline PU algorithms, as seen in the references [15] and [38]. Fig.…”

Section: A Long-baseline Interferometric Datasetmentioning

confidence: 99%

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Phase Cost Indicator-Guided Central Difference Information Filter 2-D Phase Unwrapping Approach

Zhang

Gao

et al. 2023

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Phase unwrapping (PU) as an ill-posed inverse scientific problem has invariably been the significant difficulty in interferometric synthetic aperture radar (InSAR) technique for topographic mapping. Conventional PU approaches may produce a local or global unwrapping bias in severe phase changes caused by noise and large gradient terrain because the phase continuity assumption is not satisfied. To address this issue, we have created a novel phase quality-guided integrated filtering and unwrapping process for PU. In particular, the PU path is guided by an innovative phase cost indicator, which can automatically coordinate contributions from several phase quality estimation methods so that the unwrapping path can circumvent phase discontinuity regions and delay unwrapping these pixels. Since the central difference transform is another extra effective nonlinear transformation mode based on sigma points and only has one regulation parameter, we have employed the central difference information filter (CDIF) for the first time to realize the dynamic estimation of the unwrapped phase in the PU process. We tested the proposed approach using two real datasets with different mountainous areas. The results demonstrate that the PU accuracy of the proposed approach based on these two datasets is improved by 25.2% and 40.4% compared to the unscented information filtering (UIF) PU method, and the antinoise capacity and unwrapping efficiency of the CDIF are both slightly superior to the UIF.

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Section: ⅴ Discussionsupporting

confidence: 53%

Section: A Long-baseline Interferometric Datasetmentioning

confidence: 92%

Section: Introductionmentioning

confidence: 94%