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Development of modal own embedding type reduction image codebook and highly magnifying image expansion based on fuzzy inference

Research Project

Project/Area Number 24300092
Research Category

Grant-in-Aid for Scientific Research (B)

Allocation TypePartial Multi-year Fund
Section一般
Research Field Sensitivity informatics/Soft computing
Research InstitutionKyushu Institute of Information Sciences

Principal Investigator

ASO Takashi  九州情報大学, 経営情報学部, 教授 (20259683)

Co-Investigator(Kenkyū-buntansha) CHA Byungki  九州情報大学, 経営情報学部, 教授 (10310004)
SUETAKE Noriaki  山口大学, 大学院理工学研究科, 准教授 (80334051)
KAWANO Hideaki  九州工業大学, 大学院工学研究院電気電子工学研究系, 准教授 (00404096)
TAMUKOH Hakaru  九州工業大学, 大学院生命体工学研究科, 准教授 (90432955)
Research Collaborator KUBOTA Ryosuke  
Project Period (FY) 2012-04-01 – 2015-03-31
Project Status Completed (Fiscal Year 2014)
Budget Amount *help
¥17,940,000 (Direct Cost: ¥13,800,000、Indirect Cost: ¥4,140,000)
Fiscal Year 2014: ¥6,500,000 (Direct Cost: ¥5,000,000、Indirect Cost: ¥1,500,000)
Fiscal Year 2013: ¥5,720,000 (Direct Cost: ¥4,400,000、Indirect Cost: ¥1,320,000)
Fiscal Year 2012: ¥5,720,000 (Direct Cost: ¥4,400,000、Indirect Cost: ¥1,320,000)
Keywordsファジィ推論 / 映像拡大処理 / コードブック
Outline of Final Research Achievements

While many displays are higher resolution, the measure increases in storage of a high resolution image and a physical load of transmission, and is urgently needed. This research proposes the new framework to get a high resolution image from a little low resolution image of preservation and a transmission load by highly magnifying expansion. When premising that there is a high resolution image in hand and changing a high resolution image to a low resolution image by this structure, when magnifying the ingredient expansion processing can't restore with to be embedded, it's compensated by read information. It's preliminary to the reduction image which becomes a starting point by the codebook image expansion way to which the fuzzy inference that we have developed it so far was applied. High quality of image quality in the highly magnifying image expansion which was to do a device, and was difficult up to was achieved.

Report

(4 results)
  • 2014 Annual Research Report   Final Research Report ( PDF )
  • 2013 Annual Research Report
  • 2012 Annual Research Report

Research Products

(4 results)

All 2013 2012 Other

All Journal Article (1 results) (of which Peer Reviewed: 1 results) Presentation (3 results)

  • [Journal Article] Fast Image-enlargement Algorithm for the Augmentation of the High-Frequency Component by Employing a Hierarchical Predefined Codebook2013

    • Author(s)
      Hakaru Tamukoh.Hideaki Kawano, Noriaki Suetake, Byungki Cha, Takashi Aso
    • Journal Title

      International Journal of Innovat ive Computing, Information and Control

      Volume: Vol.9 Pages: 903-914

    • Related Report
      2012 Annual Research Report
    • Peer Reviewed
  • [Presentation] A Data Embedded Reduction Image Generation Method for High-Quali ty Image Enlargement2013

    • Author(s)
      Hakaru Tamukoh.Hideaki Kawano, Noriaki Suetake.Byungki Cha, Takashi Aso
    • Organizer
      WSEAS2013
    • Place of Presentation
      ミラノ
    • Year and Date
      2013-01-09
    • Related Report
      2012 Annual Research Report
  • [Presentation] 高精細画像拡大のための情報埋込型画像縮小2012

    • Author(s)
      田向権, 河野英昭, 末竹規哲, 関根優年, 車炳王己, 麻生隆史
    • Organizer
      電子情報通信学会SIS研究会
    • Place of Presentation
      鳥取県関西本部交流室 (大阪梅田)
    • Year and Date
      2012-09-20
    • Related Report
      2012 Annual Research Report
  • [Presentation] Fuzzy-Rule-Embedded Reduction Image Construction Method for Image Enlargement with High Magnification

    • Author(s)
      Hakaru Tamukoh,Noriaki Suetake,Hideaki Kawano,Ryosuke Kubota,Byungki Cha,Takashi Aso
    • Organizer
      VISAPP2014
    • Place of Presentation
      ポルトガル,リスボン,Sana Lisbon Hotel
    • Related Report
      2013 Annual Research Report

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Published: 2012-04-23   Modified: 2019-07-29  

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