A Note on Visual Semantics in SAR 3D Imaging

HU Zhanyi

doi:10.12000/JR21149

Volume 11 Issue 1

Feb. 2022

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Article Navigation > Journal of Radars > 2022 > 11(1): 20-26

FANG Linlin, ZHOU Chao, WANG Rui, et al. RCS feature-aided insect target tracking algorithm[J]. Journal of Radars, 2019, 8(5): 598–605. doi: 10.12000/JR19067

Citation:

HU Zhanyi. A note on visual semantics in SAR 3D imaging[J]. Journal of Radars, 2022, 11(1): 20–26. doi: 10.12000/JR21149

FANG Linlin, ZHOU Chao, WANG Rui, et al. RCS feature-aided insect target tracking algorithm[J]. Journal of Radars, 2019, 8(5): 598–605. doi: 10.12000/JR19067

Citation:

HU Zhanyi. A note on visual semantics in SAR 3D imaging[J]. Journal of Radars, 2022, 11(1): 20–26. doi: 10.12000/JR21149

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A Note on Visual Semantics in SAR 3D Imaging

DOI: 10.12000/JR21149

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
Received Date: 2021-10-09
Accepted Date: 2021-11-23
Rev Recd Date: 2021-11-20

Available Online: 2021-11-25

Publish Date: 2021-12-10

Abstract

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

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References(21)

References

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