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Proposal of Singular-Unit Restoration by Focusing on the Spatial Continuity of Topographical Statistics in Spectral Domain

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Book cover Neural Information Processing (ICONIP 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9950))

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Abstract

An interferogram which interferometric synthetic aperture radar (InSAR) acquires includes singular points (SPs), which cause an unwrapping error. It is very important to remove the SP. We propose a filtering technique in order to eliminate the distortion around a SP. In this proposed filter, a complex-valued neural network (CVNN) learns the continuous changes of topographical statistics in the spectral domain. CVNN predicts the spectrum around a singular unit (SU), i.e., the four pixels constituting a SP, to restore the SU. The proposed method is so effective in the removal of the distortion at the SU that it allows us to generate a highly accurate digital elevation model (DEM).

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Authors and Affiliations

  1. Department of Electrical and Electronic Engineering, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8654, Japan

    Kazuhide Ichikawa & Akira Hirose

Authors
  1. Kazuhide Ichikawa
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  2. Akira Hirose
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Corresponding author

Correspondence to Akira Hirose .

Editor information

Editors and Affiliations

  1. The University of Tokyo , Tokyo, Japan

    Akira Hirose

  2. Kobe University , Kobe, Japan

    Seiichi Ozawa

  3. Okinawa Institute of Science and Technology Graduate University, Onna, Japan

    Kenji Doya

  4. Nara Institute of Science and Technology , Ikoma, Japan

    Kazushi Ikeda

  5. Kyungpook National University , Daegu, Korea (Republic of)

    Minho Lee

  6. Chinese Academy of Sciences , Beijing, China

    Derong Liu

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Ichikawa, K., Hirose, A. (2016). Proposal of Singular-Unit Restoration by Focusing on the Spatial Continuity of Topographical Statistics in Spectral Domain. In: Hirose, A., Ozawa, S., Doya, K., Ikeda, K., Lee, M., Liu, D. (eds) Neural Information Processing. ICONIP 2016. Lecture Notes in Computer Science(), vol 9950. Springer, Cham. https://doi.org/10.1007/978-3-319-46681-1_10

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  • DOI: https://doi.org/10.1007/978-3-319-46681-1_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-46680-4

  • Online ISBN: 978-3-319-46681-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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