Light field multi-view video coding with two-directional parallel inter-view prediction

Journal Publication ResearchOnline@JCU
Wang, Gengkun;Xiang, Wei;Pickering, Mark;Chen, Chang Wen
Abstract

Light field (LF) technology has been popularly adopted by a wide range of conventional industries. However, one problem when dealing with LFs is the sheer size of data volume. There have been many multi-view video coding (MVC)-based LF video coding methods reported in the literature, aiming at finding the best prediction structure for LF video coding. It is clear that the number of possible prediction structures is unlimited, and it is also observed that the coding bit-rate can be reduced by increasing the number of bi-directionally encoded views in the prediction structure. However, none work has been conducted to analyze the relationship of the prediction structure with its coding performance. In light of this observation, we first design a new LF-MVC prediction structure by extending the inter-view prediction into a two-directional parallel structure. Analytical models for source coding rate and encoding time are developed to analyze their relationships with the prediction structure, and are proven to be well-matched to our experimental results. Experimental evaluation of two LF video sequences demonstrates that the proposed LF-MVC prediction structure can achieve a factor of 26% bit-rate reduction against the conventional MVC prediction structure for an LF video with 5 × 5 views, and a further 34% bit-rate reduction for an LF video with a larger 10 × 10 views. Compared with the state-of-the-art MVC-based LF video coding prediction struc- tures in the literature, LF-MVC can achieve the best coding performance, and with its high encoding efficiency, is well suited for deployment in practical LF-based 3D systems.

Journal

IEEE Transactions on Image Processing

Publication Name

IEEE Transactions on Image Processing

Volume

25

ISBN/ISSN

1941-0042

Edition

N/A

Issue

11

Pages Count

14

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Publisher

IEEE

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Publisher Location

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Date

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EISSN

N/A

DOI

10.1109/TIP.2016.2603602