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Towards a generic compression solution for densely and sparsely sampled light field data
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Systems and Technology. (Realistic3D)
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Systems and Technology. (Realistic3D)
Mid Sweden University, Faculty of Science, Technology and Media, Department of Information Systems and Technology. (Realistic3D)
2018 (English)In: Proceedings of 25TH IEEE International Conference On Image Processing, 2018, p. 654-658, article id 8451051Conference paper, Published paper (Refereed)
Abstract [en]

Light field (LF) acquisition technologies capture the spatial and angular information present in scenes. The angular information paves the way for various post-processing applications such as scene reconstruction, refocusing, and synthetic aperture. The light field is usually captured by a single plenoptic camera or by multiple traditional cameras. The former captures a dense LF, while the latter captures a sparse LF. This paper presents a generic compression scheme that efficiently compresses both densely and sparsely sampled LFs. A plenoptic image is converted into sub-aperture images, and each sub-aperture image is interpreted as a frame of a multiview sequence. In comparison, each view of the multi-camera system is treated as a frame of a multi-view sequence. The multi-view extension of high efficiency video coding (MVHEVC) is used to encode the pseudo multi-view sequence.This paper proposes an adaptive prediction and rate allocation scheme that efficiently compresses LF data irrespective of the acquisition technology used.

Place, publisher, year, edition, pages
2018. p. 654-658, article id 8451051
Keywords [en]
Light field, plenoptic, Multi-camera, MVHEVC
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:miun:diva-34283DOI: 10.1109/ICIP.2018.8451051ISI: 000455181500132Scopus ID: 2-s2.0-85062918597ISBN: 978-1-4799-7061-2 (print)OAI: oai:DiVA.org:miun-34283DiVA, id: diva2:1240218
Conference
25TH IEEE International Conference On Image Processing (ICIP), Athens, Greece, October 7-10, 2018
Funder
EU, Horizon 2020Available from: 2018-08-20 Created: 2018-08-20 Last updated: 2019-03-25

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fulltext(219 kB)242 downloads
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Ahmad, WaqasOlsson, RogerSjöström, Mårten

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