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Image Super-Resolution

Spatial and Angular Reconstruction of Light field Based on Deep Generative Networks


Light field (LF) cameras often have significant limitations in spatial and angular resolutions due to their design. Many techniques that attempt to reconstruct LF images at a higher resolution only consider either spatial or angular resolution, but not both. We propose a generative network using high-dimensional convolution to improve both aspects. Our experimental results on both synthetic and real-world data demonstrate that the proposed model outperforms existing state-of-the-art methods in terms of both peak signal-to-noise ratio (PSNR) and visual quality.

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Authors:
Nan Meng, Tianjiao Zeng, Edmund Y. Lam
Submitted On:
13 September 2019 - 9:14am
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[1] Nan Meng, Tianjiao Zeng, Edmund Y. Lam, "Spatial and Angular Reconstruction of Light field Based on Deep Generative Networks", IEEE SigPort, 2019. [Online]. Available: http://sigport.org/4612. Accessed: Nov. 20, 2019.
@article{4612-19,
url = {http://sigport.org/4612},
author = {Nan Meng; Tianjiao Zeng; Edmund Y. Lam },
publisher = {IEEE SigPort},
title = {Spatial and Angular Reconstruction of Light field Based on Deep Generative Networks},
year = {2019} }
TY - EJOUR
T1 - Spatial and Angular Reconstruction of Light field Based on Deep Generative Networks
AU - Nan Meng; Tianjiao Zeng; Edmund Y. Lam
PY - 2019
PB - IEEE SigPort
UR - http://sigport.org/4612
ER -
Nan Meng, Tianjiao Zeng, Edmund Y. Lam. (2019). Spatial and Angular Reconstruction of Light field Based on Deep Generative Networks. IEEE SigPort. http://sigport.org/4612
Nan Meng, Tianjiao Zeng, Edmund Y. Lam, 2019. Spatial and Angular Reconstruction of Light field Based on Deep Generative Networks. Available at: http://sigport.org/4612.
Nan Meng, Tianjiao Zeng, Edmund Y. Lam. (2019). "Spatial and Angular Reconstruction of Light field Based on Deep Generative Networks." Web.
1. Nan Meng, Tianjiao Zeng, Edmund Y. Lam. Spatial and Angular Reconstruction of Light field Based on Deep Generative Networks [Internet]. IEEE SigPort; 2019. Available from : http://sigport.org/4612