Light-field compression using a pair of steps and depth estimation

Huang, X; An, P; Cao, F; Liu, D; Wu, Q

Light-field compression using a pair of steps and depth estimation

Huang, X An, P Cao, F Liu, D Wu, Q

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Publication Type:: Journal Article
Citation:: Optics Express, 2019, 27 (3), pp. 3557 - 3573
Issue Date:: 2019-02-04

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Field	Value	Language
dc.contributor.author	Huang, X	en_US
dc.contributor.author	An, P	en_US
dc.contributor.author	Cao, F	en_US
dc.contributor.author	Liu, D	en_US
dc.contributor.author	Wu, Q https://orcid.org/0000-0001-5641-2483	en_US
dc.date.issued	2019-02-04	en_US
dc.identifier.citation	Optics Express, 2019, 27 (3), pp. 3557 - 3573	en_US
dc.identifier.uri	http://hdl.handle.net/10453/136067
dc.description.abstract	© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement. Advanced handheld plenoptic cameras are being rapidly developed to capture information about light fields (LFs) from the 3D world. Rich LF data can be used to develop dense sub-aperture images (SAIs) that can provide a more immersive experience for users. Unlike conventional 2D images, 4D SAIs contain both the positional and directional information of light rays; the practical applications of handheld plenoptic cameras are limited by the huge volume of data required to capture this information. Therefore, an efficient LF compression method is vital for further application of the cameras. To this end, the pair of steps and depth estimation (PoS&DE) method is proposed in this paper, and the multiview video and depth (MVD) coding structure is used to relieve the LF coding burden. More specifically, a precise depth-estimation approach is presented for SAIs based on the cost function, and an SAI-guided depth optimization algorithm is designed to refine the initial depth map based on pixel variation tendency. Meanwhile, to reduce running time, intermediate SAI synthesis quality and coding bitrates, including the key SAIs selected and cost-computation steps, are set via extensive statistical experiments. In this way, only a limited number of optimally selected SAIs and their corresponding depth maps must be encoded. The experimental results demonstrate that our proposed LF compression solution using PoS&DE can obtain a satisfied coding performance.	en_US
dc.relation.ispartof	Optics Express	en_US
dc.relation.isbasedon	10.1364/OE.27.003557	en_US
dc.rights	© 2019 Optical Society of America. Users may use, reuse, and build upon the article, or use the article for text or data mining, so long as such uses are for non-commercial purposes and appropriate attribution is maintained. All other rights are reserved.	en_US
dc.rights	info:eu-repo/semantics/openAccess
dc.subject.classification	Optics	en_US
dc.title	Light-field compression using a pair of steps and depth estimation	en_US
dc.type	Journal Article
utslib.citation.volume	3	en_US
utslib.citation.volume	27	en_US
utslib.for	0205 Optical Physics	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
utslib.for	1005 Communications Technologies	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
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/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
utslib.copyright.status	open_access	*
pubs.issue	3	en_US
pubs.publication-status	Published	en_US
pubs.volume	27	en_US

Abstract:

© 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement. Advanced handheld plenoptic cameras are being rapidly developed to capture information about light fields (LFs) from the 3D world. Rich LF data can be used to develop dense sub-aperture images (SAIs) that can provide a more immersive experience for users. Unlike conventional 2D images, 4D SAIs contain both the positional and directional information of light rays; the practical applications of handheld plenoptic cameras are limited by the huge volume of data required to capture this information. Therefore, an efficient LF compression method is vital for further application of the cameras. To this end, the pair of steps and depth estimation (PoS&DE) method is proposed in this paper, and the multiview video and depth (MVD) coding structure is used to relieve the LF coding burden. More specifically, a precise depth-estimation approach is presented for SAIs based on the cost function, and an SAI-guided depth optimization algorithm is designed to refine the initial depth map based on pixel variation tendency. Meanwhile, to reduce running time, intermediate SAI synthesis quality and coding bitrates, including the key SAIs selected and cost-computation steps, are set via extensive statistical experiments. In this way, only a limited number of optimally selected SAIs and their corresponding depth maps must be encoded. The experimental results demonstrate that our proposed LF compression solution using PoS&DE can obtain a satisfied coding performance.

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http://hdl.handle.net/10453/136067