Open AccessSingle-shot compressed ultrafast photography based on U-net network
Author(s) -
Anke Zhang,
Jiamin Wu,
Jinli Suo,
Lü Fang,
Hui Qiao,
David Li,
Shian Zhang,
Jun Fan,
Dalong Qi,
Qionghai Dai,
Changxing Pei
Publication year - 2020
Publication title -
optics express
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.398083
Subject(s) - compressed sensing , ultrashort pulse , optics , photography , computer science , distortion (music) , deconvolution , artificial intelligence , digital micromirror device , femtosecond , noise (video) , single shot , shot noise , computer vision , laser , physics , image (mathematics) , telecommunications , art , amplifier , bandwidth (computing) , detector , visual arts
The compressive ultrafast photography (CUP) has achieved real-time femtosecond imaging based on the compressive-sensing methods. However, the reconstruction performance usually suffers from artifacts brought by strong noise, aberration, and distortion, which prevents its applications. We propose a deep compressive ultrafast photography (DeepCUP) method. Various numerical simulations have been demonstrated on both the MNIST and UCF-101 datasets and compared with other state-of-the-art algorithms. The result shows that our DeepCUP has a superior performance in both PSNR and SSIM compared to previous compressed-sensing methods. We also illustrate the outstanding performance of the proposed method under system errors and noise in comparison to other methods.