A Novel Light Field Image Compression Method Using EPI Restoration Neural Network.

Different from traditional images, light field images record not only spatial information but also angle information. Due to the large volume of light field data brings great difficulties to storage and compression, light field compression technology has attracted much attention. The epipolar plane...

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Detalles Bibliográficos
Publicado en:BioMed Research International pp. 1 - 9
Autores principales: Liu, Jinghuai, Zhang, Qian, Shen, Ang, Gao, Ying, Hou, Jiaqi, Wang, Bin, Yan, Tao
Formato: equations & formulas pictorial research tables/charts Journal Article
Publicado: Wiley-Blackwell 6/13/2022
Acceso en línea:Ver este registro en EBSCOhost
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      pub: Wiley-Blackwell
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        10.1155/2022/8324438
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        atl: A Novel Light Field Image Compression Method Using EPI Restoration Neural Network.
      aug:
        au:
          Liu, Jinghuai
          Zhang, Qian
          Shen, Ang
          Gao, Ying
          Hou, Jiaqi
          Wang, Bin
          Yan, Tao
        affil: College of Information, Mechanical and Electrical Engineering, Shanghai Normal University, Shanghai 200234, China
      sug:
        subj:
          Light
          Neural Networks (Computer)
          Photography
          Quantitative Studies
          Comparative Studies
          Algorithms
          Image Processing, Computer Assisted
          Qualitative Studies
      ab: Different from traditional images, light field images record not only spatial information but also angle information. Due to the large volume of light field data brings great difficulties to storage and compression, light field compression technology has attracted much attention. The epipolar plane image (EPI) contains a lot of low rank information, which is suitable for recovering the complete EPI from a part of EPI. In this paper, a light field image coding framework based on EPI restoration neural network has been proposed. Compared with previous algorithms, the proposed algorithm further takes advantage of the inherent similarity in light field images, and the proposed framework has higher performance and robustness. Experimental results show that the proposed method has superior performance compared to the state-of-the-art both in quantitatively and qualitatively.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        pictorial
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
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