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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
Autores principales: Liu, Jinghuai, Zhang, Qian, Shen, Ang, Gao, Ying, Hou, Jiaqi, Wang, Bin, Yan, Tao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9209000/
https://www.ncbi.nlm.nih.gov/pubmed/35734347
http://dx.doi.org/10.1155/2022/8324438
Descripción
Sumario: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.