Light Field Compression Using Global Multiplane Representation and Two-Step Prediction

Chen, Y; An, P; Huang, X; Yang, C; Liu, D; Wu, Q

Light Field Compression Using Global Multiplane Representation and Two-Step Prediction

Chen, Y An, P Huang, X Yang, C Liu, D Wu, Q

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Publisher:: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Publication Type:: Journal Article
Citation:: IEEE Signal Processing Letters, 2020, 27, pp. 1135-1139
Issue Date:: 2020-01-01

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Field	Value	Language
dc.contributor.author	Chen, Y
dc.contributor.author	An, P
dc.contributor.author	Huang, X
dc.contributor.author	Yang, C
dc.contributor.author	Liu, D
dc.contributor.author	Wu, Q https://orcid.org/0000-0001-5641-2483
dc.date.accessioned	2021-02-24T21:58:33Z
dc.date.available	2021-02-24T21:58:33Z
dc.date.issued	2020-01-01
dc.identifier.citation	IEEE Signal Processing Letters, 2020, 27, pp. 1135-1139
dc.identifier.issn	1070-9908
dc.identifier.issn	1558-2361
dc.identifier.uri	http://hdl.handle.net/10453/146425
dc.description.abstract	© 1994-2012 IEEE. Due to its spatio-angular structure, light field image allows for a wealth of post-processing techniques like digital refocusing and depth estimation. In order to compress the data of the two domains, the current proposal intends to embed the disparity-based view synthesis method into the decoder. However, predicting each view separately or in local groups means bringing more computational burden to the decoder and destroying the light field structure. Since disparity contains the relationship between all light rays in the light field, the proposed solution is to predict a disparity-based global representation as the first step. In the second step, all the views can be predicted easily based on this representation. In this letter, we use the recently proposed multiplane as the form of this global representation. The experimental results show the effectiveness of the proposed solution, and the better RD performance compared to other schemes especially under low bitrates.
dc.language	English
dc.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.relation.ispartof	IEEE Signal Processing Letters
dc.relation.isbasedon	10.1109/LSP.2020.3003533
dc.rights	© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject	0801 Artificial Intelligence and Image Processing, 0906 Electrical and Electronic Engineering, 1005 Communications Technologies
dc.subject.classification	Networking & Telecommunications
dc.title	Light Field Compression Using Global Multiplane Representation and Two-Step Prediction
dc.type	Journal Article
utslib.citation.volume	27
utslib.for	0801 Artificial Intelligence and Image Processing
utslib.for	0906 Electrical and Electronic Engineering
utslib.for	1005 Communications Technologies
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney
utslib.copyright.status	closed_access	*
dc.date.updated	2021-02-24T21:58:31Z
pubs.publication-status	Published
pubs.volume	27

Abstract:

© 1994-2012 IEEE. Due to its spatio-angular structure, light field image allows for a wealth of post-processing techniques like digital refocusing and depth estimation. In order to compress the data of the two domains, the current proposal intends to embed the disparity-based view synthesis method into the decoder. However, predicting each view separately or in local groups means bringing more computational burden to the decoder and destroying the light field structure. Since disparity contains the relationship between all light rays in the light field, the proposed solution is to predict a disparity-based global representation as the first step. In the second step, all the views can be predicted easily based on this representation. In this letter, we use the recently proposed multiplane as the form of this global representation. The experimental results show the effectiveness of the proposed solution, and the better RD performance compared to other schemes especially under low bitrates.

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http://hdl.handle.net/10453/146425