@inproceedings{9ac47dae4023485597c702982c9a1093,
title = "Fast object reconstruction in block-based compressive low-light-level imaging",
abstract = "In this paper, fast object reconstruction is studied for block-based compressive low-light-level imaging (BCLimaging). Instead of object pixels, linear combinations of object pixels, referred to as features, are magnified by an intensifier or MCP, and then collected as system measurements. Gaussian random projection and measurement SNR sorted Hadamard projection are studied. Then linear Wiener operator and nonlinear OMP method using parallel computing with GPU and serial process with CPU are used for reconstruction. With the help of GPU, more than 100X acceleration and less than 3ms precessing time is obtained for object reconstruction using Wiener operator.",
keywords = "Block-wised compressive imaging, Compressive imaging, GPU, Low-light-level imaging, Parallel computing",
author = "Jun Ke and Dong Sui and Ping Wei",
note = "Publisher Copyright: {\textcopyright} 2014 SPIE.; International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, IPTA 2014 ; Conference date: 13-05-2014 Through 15-05-2014",
year = "2014",
doi = "10.1117/12.2073123",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Gaurav Sharma and Fugen Zhou",
booktitle = "International Symposium on Optoelectronic Technology and Application 2014",
address = "United States",
}