Precise Markov random field model-based phase unwrapping method for airborne interferometric synthetic aperture radar imaging

Bin Zhang; Lideng Wei; Shuang Li; Qingrong Hu

doi:10.1117/1.JRS.12.035019

24 September 2018 Precise Markov random field model-based phase unwrapping method for airborne interferometric synthetic aperture radar imaging

Bin Zhang, Lideng Wei, Shuang Li, Qingrong Hu

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 12, Issue 3, 035019 (September 2018). https://doi.org/10.1117/1.JRS.12.035019

Abstract

Markovian model approach with graph cuts is effectively applied for phase unwrapping (PU) in interferometric synthetic aperture radar (InSAR) domain particularly for data with big noises and discontinuities. The first-order prior model in Markov random field (MRF) is widely used in Markovian model approach, which is able to solve PU problem in homogeneous scenarios. However, the first-order MRF method cannot interpret local details well in abundant patterns of interferograms under the requirement of high accuracy due to the limitation of first-order prior information. Hence, the conventional first-order model is no longer applicable in this situation. In terms of this problem, the shortcoming of the first-order model is analyzed, and a precise second-order MRF approach is proposed in this paper. Furthermore, a graph cuts-based optimization PU algorithm is designed under a high-order MRF mode, which improves the PU accuracy in detail areas. Without apparent increase of computational complexity, the proposed method is more robust compared with the conventional first-order MRF-based methods. A set of experimental results on both simulation and real measured millimeter-wave InSAR data illustrate the effectiveness of the proposal.

Citation Download Citation

Bin Zhang, Lideng Wei, Shuang Li, and Qingrong Hu "Precise Markov random field model-based phase unwrapping method for airborne interferometric synthetic aperture radar imaging," Journal of Applied Remote Sensing 12(3), 035019 (24 September 2018). https://doi.org/10.1117/1.JRS.12.035019

Received: 20 May 2018; Accepted: 4 September 2018; Published: 24 September 2018

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