Towards reconstructing HDR light fields by combining 2D and 3D CNN architectures

Mary Guindy, Vamsi Kiran Adhikarla, Peter Andras Kara, Tibor Balogh, Aniko Simon

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Abstract

High dynamic range imaging has recently become a technological trend, with numerous attempts to reconstruct HDR images and videos from low-dynamic-range data. The reconstruction of light field images is analogous to the reconstruction of HDR videos, within which consecutive frames are temporally coherent. For light field images, many similarities exist between the adjacent views, since they visualize the same scene from different angular perspectives. In this paper, we investigate the theoretical possibilities of combining CNN architectures utilized for HDR images and videos in order to enhance the outputs of HDR light field image reconstruction.
Original languageEnglish
Title of host publicationPublished in: Proceedings Volume 12097, Big Data IV: Learning, Analytics, and Applications; (2022), ISSN 0277-786X, ISBN 9781510650701, article no. 120970M. Organising Body: SPIE Organising Body: SPIE
DOIs
Publication statusPublished - 4 Apr 2022
Externally publishedYes

Bibliographical note

Note: Published in: Proceedings Volume 12097, Big Data IV: Learning, Analytics, and Applications; (2022), ISSN 0277-786X,
ISBN 9781510650701, article no. 120970M.

Organising Body: SPIE

Organising Body: SPIE

Keywords

  • Computer science and informatics

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  • Towards reconstructing HDR light fields by combining 2D and 3D CNN architectures

    Guindy, M., Adhikarla, V. K., Kara, P. A., Balogh, T. & Simon, A., 4 Apr 2022.

    Research output: Contribution to conferencePaperpeer-review

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