Light field image coding based on hybrid data representation

Bibliographic Details
Main Author: Monteiro, R.
Publication Date: 2020
Other Authors: Rodrigues, N., Faria, S. M. M., Nunes, P.
Format: Article
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10071/20633
Summary: This paper proposes a novel efficient light field coding approach based on a hybrid data representation. Current state-of-the-art light field coding solutions either operate on micro-images or sub-aperture images. Consequently, the intrinsic redundancy that exists in light field images is not fully exploited, as is demonstrated. This novel hybrid data representation approach allows to simultaneously exploit four types of redundancies: i) sub-aperture image intra spatial redundancy, ii) sub-aperture image inter-view redundancy, iii) intra-micro-image redundancy, and iv) inter-micro-image redundancy between neighboring micro-images. The proposed light field coding solution allows flexibility for several types of baselines, by adaptively exploiting the most predominant type of redundancy on a coding block basis. To demonstrate the efficiency of using a hybrid representation, this paper proposes a set of efficient pixel prediction methods combined with a pseudo-video sequence coding approach, based on the HEVC standard. Experimental results show consistent average bitrate savings when the proposed codec is compared to relevant state-of-the-art benchmarks. For lenslet light field content, the proposed coding algorithm outperforms the HEVC-based pseudo-video sequence coding benchmark by an average bitrate savings of 23%. It is shown for the same light field content that the proposed solution outperforms JPEG Pleno verification models MuLE and WaSP, as these codecs are only able to achieve 11% and -14% bitrate savings over the same HEVC-based benchmark, respectively. The performance of the proposed coding approach is also validated for light fields with wider baselines, captured with high-density camera arrays, being able to outperform both the HEVC-based benchmark, as well as MuLE and WaSP.
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spelling Light field image coding based on hybrid data representationHEVCLight field representationLight field image codingPseudo-video sequenceSpatial pixel predictionLeast squares predictionThis paper proposes a novel efficient light field coding approach based on a hybrid data representation. Current state-of-the-art light field coding solutions either operate on micro-images or sub-aperture images. Consequently, the intrinsic redundancy that exists in light field images is not fully exploited, as is demonstrated. This novel hybrid data representation approach allows to simultaneously exploit four types of redundancies: i) sub-aperture image intra spatial redundancy, ii) sub-aperture image inter-view redundancy, iii) intra-micro-image redundancy, and iv) inter-micro-image redundancy between neighboring micro-images. The proposed light field coding solution allows flexibility for several types of baselines, by adaptively exploiting the most predominant type of redundancy on a coding block basis. To demonstrate the efficiency of using a hybrid representation, this paper proposes a set of efficient pixel prediction methods combined with a pseudo-video sequence coding approach, based on the HEVC standard. Experimental results show consistent average bitrate savings when the proposed codec is compared to relevant state-of-the-art benchmarks. For lenslet light field content, the proposed coding algorithm outperforms the HEVC-based pseudo-video sequence coding benchmark by an average bitrate savings of 23%. It is shown for the same light field content that the proposed solution outperforms JPEG Pleno verification models MuLE and WaSP, as these codecs are only able to achieve 11% and -14% bitrate savings over the same HEVC-based benchmark, respectively. The performance of the proposed coding approach is also validated for light fields with wider baselines, captured with high-density camera arrays, being able to outperform both the HEVC-based benchmark, as well as MuLE and WaSP.IEEE2020-07-23T15:11:46Z2020-01-01T00:00:00Z20202020-07-23T16:10:53Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/20633eng2169-353610.1109/ACCESS.2020.3004625Monteiro, R.Rodrigues, N.Faria, S. M. M.Nunes, P.info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-07-07T02:31:59Zoai:repositorio.iscte-iul.pt:10071/20633Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T18:00:06.956188Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Light field image coding based on hybrid data representation
title Light field image coding based on hybrid data representation
spellingShingle Light field image coding based on hybrid data representation
Monteiro, R.
HEVC
Light field representation
Light field image coding
Pseudo-video sequence
Spatial pixel prediction
Least squares prediction
title_short Light field image coding based on hybrid data representation
title_full Light field image coding based on hybrid data representation
title_fullStr Light field image coding based on hybrid data representation
title_full_unstemmed Light field image coding based on hybrid data representation
title_sort Light field image coding based on hybrid data representation
author Monteiro, R.
author_facet Monteiro, R.
Rodrigues, N.
Faria, S. M. M.
Nunes, P.
author_role author
author2 Rodrigues, N.
Faria, S. M. M.
Nunes, P.
author2_role author
author
author
dc.contributor.author.fl_str_mv Monteiro, R.
Rodrigues, N.
Faria, S. M. M.
Nunes, P.
dc.subject.por.fl_str_mv HEVC
Light field representation
Light field image coding
Pseudo-video sequence
Spatial pixel prediction
Least squares prediction
topic HEVC
Light field representation
Light field image coding
Pseudo-video sequence
Spatial pixel prediction
Least squares prediction
description This paper proposes a novel efficient light field coding approach based on a hybrid data representation. Current state-of-the-art light field coding solutions either operate on micro-images or sub-aperture images. Consequently, the intrinsic redundancy that exists in light field images is not fully exploited, as is demonstrated. This novel hybrid data representation approach allows to simultaneously exploit four types of redundancies: i) sub-aperture image intra spatial redundancy, ii) sub-aperture image inter-view redundancy, iii) intra-micro-image redundancy, and iv) inter-micro-image redundancy between neighboring micro-images. The proposed light field coding solution allows flexibility for several types of baselines, by adaptively exploiting the most predominant type of redundancy on a coding block basis. To demonstrate the efficiency of using a hybrid representation, this paper proposes a set of efficient pixel prediction methods combined with a pseudo-video sequence coding approach, based on the HEVC standard. Experimental results show consistent average bitrate savings when the proposed codec is compared to relevant state-of-the-art benchmarks. For lenslet light field content, the proposed coding algorithm outperforms the HEVC-based pseudo-video sequence coding benchmark by an average bitrate savings of 23%. It is shown for the same light field content that the proposed solution outperforms JPEG Pleno verification models MuLE and WaSP, as these codecs are only able to achieve 11% and -14% bitrate savings over the same HEVC-based benchmark, respectively. The performance of the proposed coding approach is also validated for light fields with wider baselines, captured with high-density camera arrays, being able to outperform both the HEVC-based benchmark, as well as MuLE and WaSP.
publishDate 2020
dc.date.none.fl_str_mv 2020-07-23T15:11:46Z
2020-01-01T00:00:00Z
2020
2020-07-23T16:10:53Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
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url http://hdl.handle.net/10071/20633
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2169-3536
10.1109/ACCESS.2020.3004625
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv IEEE
publisher.none.fl_str_mv IEEE
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
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reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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