Please use this identifier to cite or link to this item:
http://hdl.handle.net/10071/22442
Author(s): | Monteiro, R. J. S. Rodrigues, N. M. M. Faria, S. M. M. Nunes, P. J. L. |
Date: | 2021 |
Title: | Light field image coding with flexible viewpoint scalability and random access |
Volume: | 94 |
ISSN: | 0923-5965 |
DOI (Digital Object Identifier): | 10.1016/j.image.2021.116202 |
Keywords: | Light field image coding Viewpoint scalability Viewpoint random access HEVC |
Abstract: | This paper proposes a novel light field image compression approach with viewpoint scalability and random access functionalities. Although current state-of-the-art image coding algorithms for light fields already achieve high compression ratios, there is a lack of support for such functionalities, which are important for ensuring compatibility with different displays/capturing devices, enhanced user interaction and low decoding delay. The proposed solution enables various encoding profiles with different flexible viewpoint scalability and random access capabilities, depending on the application scenario. When compared to other state-of-the-art methods, the proposed approach consistently presents higher bitrate savings (44% on average), namely when compared to pseudo-video sequence coding approach based on HEVC. Moreover, the proposed scalable codec also outperforms MuLE and WaSP verification models, achieving average bitrate saving gains of 37% and 47%, respectively. The various flexible encoding profiles proposed add fine control to the image prediction dependencies, which allow to exploit the tradeoff between coding efficiency and the viewpoint random access, consequently, decreasing the maximum random access penalties that range from 0.60 to 0.15, for lenslet and HDCA light fields. |
Peerreviewed: | yes |
Access type: | Open Access |
Appears in Collections: | IT-RI - Artigos em revistas científicas internacionais com arbitragem científica |
Files in This Item:
File | Description | Size | Format | |
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article_81366.pdf | Versão Aceite | 1,28 MB | Adobe PDF | View/Open |
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