合成孔径雷达三维成像中的视觉语义浅析

胡占义

doi:10.12000/JR21149

合成孔径雷达三维成像中的视觉语义浅析

DOI: 10.12000/JR21149

胡占义^,

中国科学院自动化研究所模式识别国家重点实验室北京 100190

基金项目: 国家自然科学基金(61991423, 61772444)

详细信息

作者简介:
胡占义(1961–)，男，山西繁峙人，博士，研究员。1985年于北方工业大学自动化系获学士学位，1993年于比利时列日大学工学院获博士学位。1993年至今在中国科学院自动化研究所模式识别国家重点实验室工作。长期从事计算机视觉和生物视觉研究，个人网页：http://vision.ia.ac.cn/zh/faculty/zyhu/index.html

通讯作者:
胡占义 huzy@nlpr.ia.ac.cn

责任主编：丁赤飚 Corresponding Editor: DING Chibiao
中图分类号: TP391
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出版历程
- 收稿日期: 2021-10-09
- 修回日期: 2021-11-20
- 网络出版日期: 2021-12-10
- 刊出日期: 2022-02-28

A Note on Visual Semantics in SAR 3D Imaging

HU Zhanyi^,

National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China

Funds: The National Natural Science Foundation of China (61991423, 61772444)

More Information

Corresponding author: HU Zhanyi, huzy@nlpr.ia.ac.cn

摘要

摘要: “合成孔径雷达微波视觉三维成像”，从概念上说，旨在将“视觉语义”引入到合成孔径雷达的成像模型中，以期提高三维成像的质量。对层析合成孔径雷达(TomoSAR)来说， “视觉语义”的引入可望有效减少TomoSAR所需的观测次数。然而，什么是“视觉语义”？从视觉感知的途径看， “单眼”和“双眼”均可以从场景感知三维结构信息；从场景内容看，不同的人对同一幅图像会有不同感受；从视觉神经加工机理看，三维信息加工和二维信息加工也存在一些本质差异。另外，人类视觉感知普遍存在错觉(illusion)现象。那么，到底什么类型的“视觉语义信息”可望在计算的层次上有助于微波三维成像呢？如何借鉴计算机视觉的理论和方法来提取微波三维成像中有用的“视觉语义”信息呢？该文对这些问题进行了一些初步探讨。
- 视觉通道 /
- 微波视觉 /
- 层析SAR
Abstract: Conceptually speaking, Synthetic Aperture Radar (SAR) microwave vision 3D imaging refers to fusing visual semantics into the SAR 3D imaging process to enhance the 3D imaging quality. For SAR Tomography (TomoSAR), it specifically means to reduce the needed observations by fully exploiting SAR visual semantics. However, what does it mean by visual semantics? From the viewpoint of visual perception, 3D structural information could be perceived from either monocular image or binocular images and the same scene could be perceived differently by different people. From the viewpoint of neurophysiology, depth perception from binocular or monocular vision has fundamentally different mechanism. Besides visual illusion phenomenon is omnipresent in daily life. Hence what kinds of visual semantics could be helpful for SAR 3D imaging from the computational point of view? What could be learnt from computer vision community to extract useful visual semantics from SAR images? This short note presents some preliminary discussions on such issues, a purely personal view on such vast topics.
- Visual pathway /
- Microwave vision /
- TomoSAR

HTML全文

图 1 视觉腹部通道和背部通道。腹部通道主要负责物体视觉，背部通道主要负责空间视觉

Figure 1. Visual ventral pathway and dorsal pathway: Ventral pathway is mainly for object vision, dorsal pathway for spatial vision

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图 2 从线画图可以产生三维感觉^[1]

Figure 2. Human could perceive 3D shape from line drawing^[1]

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图 3 图中两个人身高感觉存在明显差异

Figure 3. The Ames room illusion. Two women in the picture have similar heights, but perceived very differently

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图 4 从图(a)可以感知到船的一些三维结构信息；图(b)可以感知到桥的一些三维结构

Figure 4. 3D ship structural information could be perceived from (a); Bridge 3D shape could be clearly perceived from (b)

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图 5 TomoSAR迭代处理框架

Figure 5. TomoSAR iterative framework

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图 6 TomoSAR的伪多尺度处理框架

Figure 6. TomoSAR pseudo-multi-scale framework

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