TY - CONF
T1 - Towards reconstructing HDR light fields by combining 2D and 3D CNN architectures
AU - Guindy, Mary
AU - Adhikarla, Vamsi Kiran
AU - Kara, Peter Andras
AU - Balogh, Tibor
AU - Simon, Aniko
N1 - 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
PY - 2022/4/4
Y1 - 2022/4/4
N2 - 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.
AB - 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.
KW - Computer science and informatics
U2 - 10.1117/12.2618993
DO - 10.1117/12.2618993
M3 - Paper
T2 - Big Data IV: Learning, Analytics, and Applications
Y2 - 3 April 2022 through 4 April 2022
ER -