A Novel PU Method for Mining Area Based on Edge Detection Using the SegNet Model

IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society Pub Date : 2024-11-04 DOI:10.1109/LGRS.2024.3490552

Baojing Zhang;Zhiyong Wang;Zhenjin Li;Wenfu Yang;Weibing Li

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Abstract

Due to the large deformation gradient caused by mining, it is easy to cause serious incoherence phenomenon in radar interferometry, and the traditional phase unwrapping (PU) method is limited in this case. To solve this problem, a novel PU method for mining area based on edge detection using the SegNet model is proposed for mining subsidence basins with large deformation. First, SegNet network was used to extract the edge information of the subsidence basin in the mining area. Then, the edges were refined and connected by the Zhang-Suen thinning method and regional growth method, respectively. Finally, PU was completed by the determined phase jump variables. Simulated interferograms with different signal-to-noise ratio (SNR) and two real interferograms with different interference qualities are selected for experiments. Compared with the three traditional PU methods and two deep learning PU methods, the proposed model has higher accuracy and better robustness. When the SNR is 1 and 4, the unwrapping error distribution area of the proposed method is the smallest, and the PU result is more close to the real situation in the interferogram of real mining area. The novel two-step PU method effectively solves the problem that the traditional PU method is seriously affected by noise and large deformation.

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使用 SegNet 模型基于边缘检测挖掘区域的新型 PU 方法

由于采矿造成的大变形梯度，在雷达干涉测量中容易造成严重的不相干现象，传统的相位解包（PU）方法在这种情况下受到限制。为解决这一问题，针对具有较大变形的采矿沉陷盆地，提出了一种基于边缘检测的 SegNet 模型的新型采空区 PU 方法。首先，使用 SegNet 网络提取采矿区沉陷盆地的边缘信息。然后，分别采用张-孙稀疏法和区域增长法对边缘进行细化和连接。最后，通过确定的相跃变量完成 PU。实验选取了不同信噪比（SNR）的模拟干涉图和两个不同干扰质量的真实干涉图。与三种传统 PU 方法和两种深度学习 PU 方法相比，所提出的模型具有更高的精度和更好的鲁棒性。当信噪比为 1 和 4 时，所提方法的解包误差分布区域最小，在真实矿区干涉图中的 PU 结果更接近真实情况；当信噪比为 1 和 4 时，所提方法的解包误差分布区域最小，在真实矿区干涉图中的 PU 结果更接近真实情况。新颖的两步 PU 方法有效地解决了传统 PU 方法受噪声和大变形影响严重的问题。

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IEEE geoscience and remote sensing letters : a publication of the IEEE Geoscience and Remote Sensing Society

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