@inproceedings{8fb7645f9f024818b6a176cd5aab1732,
title = "Fast compressive sensing of high-dimensional signals with tree-structure sparsity pattern",
abstract = "Compressive sensing of multi-dimensional signals (tensors) only receives limited attention. Separable sensing and proper sparsity pattern play two key roles for compressive sensing of tensors to be feasible and efficient. In view of inherent characteristic of 2D images and 3D videos, we propose the use of tree-structure sparsity pattern in tensor compressive sensing and develop a multiway tree-structure sparsity pattern OMP algorithm in this paper. Experimental results demonstrate the effectiveness of our method in terms of recovery quality and speed.",
author = "Lu, \{Chun Shien\} and Liang, \{Wei Jie\}",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2nd IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 ; Conference date: 09-07-2014 Through 13-07-2014",
year = "2014",
month = sep,
day = "3",
doi = "10.1109/ChinaSIP.2014.6889342",
language = "English",
series = "2014 IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "738--742",
booktitle = "2014 IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Proceedings",
address = "United States",
}