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AuthorBelhi, Abdelhak
AuthorBouras, Abdelaziz
AuthorAlfaqheri, Taha
AuthorAondoakaa, Akuha Solomon
AuthorSadka, Abdul Hamid
Available date2020-05-14T09:55:43Z
Publication Date2019
Publication NameSignal Processing: Image Communication
ResourceScopus
ISSN9235965
URIhttp://dx.doi.org/10.1016/j.image.2019.04.005
URIhttp://hdl.handle.net/10576/14819
AbstractThrough this paper, we aim at investigating the impact of using deep learning-based technologies such as super-resolution on Holoscopic 3D (H3D) images. Holoscopic 3D imaging is a technology that aims at providing cost-effective alternatives for 3D content viewing and consumption without requiring a special headgear or posture. The technique is using a special lens array fitted to standard DSLR or mirrorless cameras to generate or capture 3D content. The output is a Holoscopic 3D image that can be displayed in lightfield displays or Multiview displays following a post-processing procedure. The main advantage of this technique is its cost-effectiveness in viewing and interacting with 3D content. However, one of its drawbacks is the low spatial density of the commercial cameras CMOS sensors and the lens induced imperfections. The latter can be fixed in software using some distortion correction techniques. However, the former is still challenging in terms of techniques that result in naturally looking output. Mitigating such issues with hardware will lead to higher costs and the technique loses its main advantage. Our approach consists of designing a framework that leverages software tools in order to upscale the output of H3D cameras whilst solving the low spatial density problem of H3D images. We also investigate the impact of deep learning-based video motion interpolation on the output quality of the cultural H3D imaging framework. - 2019
SponsorThis publication was made possible by NPRP grant 9-181-1-036 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors ( www.ceproqha.qa ). The authors would also like to thank Mr. Marc Pelletreau, the MIA Multimedia team, the Art Curators and the management staff of the Museum of Islamic art, Doha Qatar for their help and contribution in the data acquisition.
Languageen
PublisherElsevier B.V.
Subject3D holoscopic imaging
Cultural heritage
Deep learning
Super-resolution
TitleInvestigating 3D holoscopic visual content upsampling using super-resolution for cultural heritage digitization
TypeArticle
Pagination188-198
Volume Number75
dc.accessType Abstract Only


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