Artigo em revista científica Q1
Light field image coding based on hybrid data representation
Ricardo Jorge Monteiro (Monteiro, R.); Nuno M. M. Rodrigues (Rodrigues, N.); Sérgio M. M. Faria (Faria, S. M. M.); Paulo Nunes (Nunes, P.);
Título Revista
IEEE Access
Ano (publicação definitiva)
2020
Língua
Inglês
País
Estados Unidos da América
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Abstract/Resumo
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.
Agradecimentos/Acknowledgements
The authors would like to thank Mr. Pekka Astola for providing the WaSP software and Dr. Eduardo Silva and Dr. Carla Pagliari for providing the MuLE software as well as contributing with insightful discussions.
Palavras-chave
HEVC,Light field representation,Light field image coding,Pseudo-video sequence,Spatial pixel prediction,Least squares prediction
  • Ciências da Computação e da Informação - Ciências Naturais
  • Engenharia Eletrotécnica, Eletrónica e Informática - Engenharia e Tecnologia
Registos de financiamentos
Referência de financiamento Entidade Financiadora
UIDB/EEA/50008/2020 Fundação para a Ciência e Tecnologia
SFRH/BD/136953/2018 Fundação para a Ciência e Tecnologia