Adaptive Subsurface 3-D Imaging Based on Peak Phase-Retrieval and Complex-Valued Self-Organizing Map

Shimomura Soshi; Hirose Akira

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Adaptive Subsurface 3-D Imaging Based on Peak Phase-Retrieval and Complex-Valued Self-Organizing Map

机译：基于峰值相检索和复合自组织地图的自适应地下3-D成像

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摘要

We propose an adaptive subsurface 3-D visualization system based on a complex-valued self-organizing map (CSOM). Conventionally buried things can be detected in the so-called B-scan images obtained by a ground penetrating radar. In contrast, our proposed method is able not only to detect their presence but also to classify the targets by the self-organizing dynamics in the CSOM. Instead of utilizing only the amplitude information in the time domain, we use both the amplitude and the phase information to obtain the scattering coefficients of scatterers by use of the phase retrieval method.

机译：我们提出了一种基于复值的自组织地图（CSOM）的自适应地下3-D可视化系统。在通过地面穿透雷达获得的所谓的B扫描图像中可以检测到常规掩埋的东西。相比之下，我们所提出的方法不仅能够检测到他们的存在，还可以通过CSOM中的自组织动态来对目标进行分类。而不是在时域中仅利用幅度信息，我们使用幅度和相位信息来通过使用相位检索方法获得散射系数的散射系数。

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来源
《IEEE Geoscience and Remote Sensing Letters》 |2020年第1期|52-56|共5页
作者
Shimomura Soshi; Hirose Akira;
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作者单位

Univ Tokyo Dept Elect & Elect Engn Tokyo 1138656 Japan;

Univ Tokyo Dept Elect & Elect Engn Tokyo 1138656 Japan|Univ Tokyo Dept Bioengn Tokyo 1138656 Japan;

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正文语种 eng
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关键词
Scattering; Time-domain analysis; Landmine detection; Frequency-domain analysis; Ground penetrating radar; Self-organizing feature maps; Directive antennas; Complex-valued self-organizing map (CSOM); cubic scan (C-scan); ground penetrating radar (GPR);

机译：散射;时间域分析;地雷检测;频域分析;地面穿透雷达;自组织特征图;指示天线;复数自组织地图（CSOM）;立方扫描（C扫描）;地面穿透雷达（GPR）;

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1. Adaptive Plastic Mine Imaging by Complex-Valued Self-Organizing Map [J] . Akira HIROSE, Takahiro HARA 電子情報通信学会技術研究報告. 宇宙·航行エレクトロニクス. Space, Aeronautical and Navigational Electronics . 2003,第300期

机译：基于复值自组织映射的自适应塑性矿井成像
2. Adaptive Plastic Mine Imaging by Complex-Valued Self-Organizing Map [J] . Akira HIROSE, Takahiro HARA 電子情報通信学会技術研究報告. 宇宙·航行エレクトロニクス. Space, Aeronautical and Navigational Electronics . 2003,第300期

机译：复杂的自组织地图的自适应塑料矿山成像
3. Fast-Learning Adaptive-Subspace Self-Organizing Map: An Application to Saliency-Based Invariant Image Feature Construction [J] . Zheng H., Lefebvre G., Laurent C. IEEE Transactions on Neural Networks . 2008,第5期

机译：快速学习的自适应子空间自组织图：在基于显着性的不变图像特征构造中的应用
4. Adaptive Subsurface Visualization System Using Phase Retrieval Method and Complex-valued Self-organizing Map [C] . S. Shimomura, A. Hirose Progress in electromagnetics research symposium . 2018

机译：相位检索和复值自组织映射的自适应地下可视化系统
5. Stereo Vision Based on Mathematical Modeling - Toward Adaptive and Precise 3-D Reconstruction from Projected Images [D] . 奥富正敏. 1993

机译：基于数学建模的立体视觉-通过投影图像实现自适应和精确的3D重建
6. MAgnitude and PHase Thresholding (MAPHT) of noisy complex-valued magnetic resonance images [O] . Daniel B. Rowe, E. Mark Haacke -1

机译：噪声复合磁共振图像的幅度和相位阈值（Mapht）
7. Fast-Learning Adaptive-Subspace Self-Organizing Map: An Application to Saliency-Based Invariant Image Feature Construction [O] . Zheng, Huicheng, Lefebvre, Grégoire, Laurent, Christophe 2008

机译：快速学习的自适应子空间自组织图：在基于显着性的不变图像特征构造中的应用

Adaptive Subsurface 3-D Imaging Based on Peak Phase-Retrieval and Complex-Valued Self-Organizing Map

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