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Multi-band Polarization Imaging and Applications pp 155–176Cite as

Bio-inspired Multi-band Polarization Imaging

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Part of the book series: Advances in Computer Vision and Pattern Recognition ((ACVPR))

Abstract

Multi-band polarization imaging has a variety of applications including land cover classification, military target detection, 3D surface reconstruction, and glare/shadow removal. A comprehensive utilization of spatial, spectral, and polarization information is effective to detect hidden or camouflaged targets which may not be discoverable by traditional optical imaging techniques. Present multi-band polarization sensors rely on dispersion, beam split or interference to obtain spectral information, while polarization information in different direction is acquired by changing polarization angles]. Acquisition of multiple images in different spectral bands and polarization angles may take a relatively long time, a large amount of data, and limited field of view. Conventional multi-band polarization imaging techniques may not satisfy the requirements in modern warfare in terms of dynamic environments, larger field of view, and fast response time. Recent research indicates that some aquatic organisms like dragonfly nymphs, mantis shrimps, and cuttlefish hunt with their multi-band polarization vision. Such observations sparked the studies on multi-band polarization imaging techniques.

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Authors and Affiliations

  1. Northwestern Polytechnical University, Xi’an, China

    Yongqiang Zhao, Chen Yi, Quan Pan & Yongmei Cheng

  2. Sejong University, Seoul, Korea, Republic of (South Korea)

    Seong G. Kong

Authors
  1. Yongqiang Zhao
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  2. Chen Yi
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  3. Seong G. Kong
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  4. Quan Pan
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  5. Yongmei Cheng
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Corresponding author

Correspondence to Yongqiang Zhao .

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© 2016 National Defense Industry Press, Beijing and Springer-Verlag Berlin Heidelberg

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Zhao, Y., Yi, C., Kong, S.G., Pan, Q., Cheng, Y. (2016). Bio-inspired Multi-band Polarization Imaging. In: Multi-band Polarization Imaging and Applications. Advances in Computer Vision and Pattern Recognition. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49373-1_6

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  • DOI: https://doi.org/10.1007/978-3-662-49373-1_6

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-49371-7

  • Online ISBN: 978-3-662-49373-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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