@inproceedings{ad7ff385dc5b4bc2b39388344186fb6e,
title = "Bayesian sparse reconstruction based on dictionary learning",
abstract = "Imaging through thick scattering media produces a random speckle signal with wealth information, which can be restored by subsequent processing. While a moving target is hard to reconstruct by existing technology, we apply temporal Bayesian compressed sensing method to overcome this limitation. In addition, an over completed dictionary is used as a sparse base to improve the accuracy of the reconstructions. In this letter, we improve system time resolution without changing its spatial resolution and reconstruct T frame speckle images from a single temporal compressed speckle measurement.",
keywords = "Bayesian Estimation, Compressed Sensing, Dictionary Learning",
author = "Yan Wang and Jun Ke",
note = "Publisher Copyright: {\textcopyright} 2020 SPIE; Advanced Optical Imaging Technologies III 2020 ; Conference date: 11-10-2020 Through 16-10-2020",
year = "2020",
doi = "10.1117/12.2575180",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Xiao-Cong Yuan and Carney, {P. Scott} and Kebin Shi",
booktitle = "Advanced Optical Imaging Technologies III",
address = "United States",
}