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2005 Fiscal Year Final Research Report Summary

A study on application of flow velocity distribution measurement of drift ice of Okhotsk coast ice sea navigation using Radar images

Research Project

Project/Area Number 16510131
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeSingle-year Grants
Section一般
Research Field Social systems engineering/Safety system
Research InstitutionKushiro National College of Technology

Principal Investigator

TAKAGI Toshiyuki  Kushiro National College of Technology, Dept. of Electrical Engineering, Dr., Prof., 電気工学科, 教授 (30331953)

Project Period (FY) 2004 – 2005
KeywordsOkhotsk sea / Radar image / Block matching method / Sub pixel / Neural networks
Research Abstract

(1)Speed-up of movement analysis of drift ice radar image
To get a time change in the drift ice distribution automatically the block match method can be applied to the drift ice radar image. However, the movement of the drift ice distribution is complex, and a lot of errors occur in a usual block match analysis. Moreover, it is necessary not only to understand a present situation to secure a safe sea route but also forecast the situation in the future. And, it is necessary to achieve this processing ideally automatically and in real time. An analytical result of the block match method can be used as input information on the forecast processing. However, because the amount of the calculation is very large in a usual block match method, real time processing is difficult. Then, to measure speeding up and making of the drift ice analysis highly accurate in this research, the improvement technique of the block match is developed.
(2)Sub-pixel estimation method using neural networks
A sub pixel estimation technique using neural networks has been presented for obtaining flow velocity distribution of sea ice. If we need precise displacement of the flow of the drift ice, sub-pixel estimation of best matching location is required. The sub-pixel accuracy is obtained by applying an interpolation scheme to the correlation peak within the interrogation area. Traditionally, the Gauss function has been used as peak-fitting function. However the sub-pixel accuracy is dependent upon both a bias error and a random error. It is very difficult to identify peak fitting function for all applied images. Then, we propose the method that uses neural networks which has a priori knowledge about applied image. We show the proposed technique achieved good results from the radar image.

  • Research Products

    (4 results)

All 2006

All Journal Article (4 results)

  • [Journal Article] A Sub-pixel Estimation of Drift Ice Motion on Radar Images using Neural Networks2006

    • Author(s)
      高木敏幸
    • Journal Title

      The 21st International Symposium on Okhotsk Sea & Sea Ice

      Pages: 103-106

    • Description
      「研究成果報告書概要(和文)」より
  • [Journal Article] 流氷レーダ画像の運動解析の高速化2006

    • Author(s)
      柳川和徳
    • Journal Title

      電子情報通信学会2006年総合大会講演論文集

      Pages: 114

    • Description
      「研究成果報告書概要(和文)」より
  • [Journal Article] A Sub-pixel Estimation of Drift Ice Motion on Radar Images using Neural Networks2006

    • Author(s)
      T.Takagi
    • Journal Title

      The 21st International Symposium on Okhotsk Sea & Sea Ice

      Pages: 103-106

    • Description
      「研究成果報告書概要(欧文)」より
  • [Journal Article] An Acceleration Scheme for Motion Analysis of Sea-Ice Radar Images2006

    • Author(s)
      Kazunori Yanagawa
    • Journal Title

      Proc. of The 2006 IEICE General Conference

      Pages: 144

    • Description
      「研究成果報告書概要(欧文)」より

URL: 

Published: 2007-12-13  

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