Light Field Spatial Super-resolution via Multi-level Perception and View Reorganization

Abstract: Light field (LF) imaging can obtain spatial and angular information of three-dimensional (3D) scene through a single shot, which enables a wide range of applications in the fields of 3D reconstruction, refocusing, virtual reality, etc. However, due to the inherent trade-off problem, the spatial resolution of acquired LF images is low, which hinders the widespread application of LF imaging technique. In order to relieve this issue, an end-to-end LF spatial super-resolution network is proposed by considering the multi-level perception and view reorganization. This method can fully explore the highly interwoven LF spatial and angular structure information. Specifically, a multi-feature fusion enhancement block is introduced that can fully perceive LF spatial, angular, and EPI information for LF spatial super-resolution. Furthermore, the angular coherence between LF views is exploited by reorganizing the LF sub-aperture images and constructing a multi-angular stack structure. Compared with other state-of-the-art methods, the proposed method achieves superior performance in both visual and quantitative terms.

Yifan Mao, Zaidong Tong, Xin Zheng, Xiaofei Zhou, Youzhi Zhang and Deyang Liu. “Light Field Spatial Super-resolution via Multi-level Perception and View Reorganization”. International Journal of Advanced Computer Science and Applications (IJACSA) 14.5 (2023). http://dx.doi.org/10.14569/IJACSA.2023.01405111

@article{Mao2023,
title = {Light Field Spatial Super-resolution via Multi-level Perception and View Reorganization},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.01405111},
url = {http://dx.doi.org/10.14569/IJACSA.2023.01405111},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {5},
author = {Yifan Mao and Zaidong Tong and Xin Zheng and Xiaofei Zhou and Youzhi Zhang and Deyang Liu}
}