Fast compressive sensing of high-dimensional signals with tree-structure sparsity pattern

Chun Shien Lu, Wei Jie Liang

研究成果: Conference contribution

5 引文 斯高帕斯(Scopus)

摘要

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.

原文English
主出版物標題2014 IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Proceedings
發行者Institute of Electrical and Electronics Engineers Inc.
頁面738-742
頁數5
ISBN(電子)9781479954032
DOIs
出版狀態Published - 2014 九月 3
事件2nd IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Xi'an, China
持續時間: 2014 七月 92014 七月 13

出版系列

名字2014 IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Proceedings

Other

Other2nd IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014
國家China
城市Xi'an
期間14-07-0914-07-13

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Signal Processing

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    Lu, C. S., & Liang, W. J. (2014). Fast compressive sensing of high-dimensional signals with tree-structure sparsity pattern. 於 2014 IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Proceedings (頁 738-742). [6889342] (2014 IEEE China Summit and International Conference on Signal and Information Processing, IEEE ChinaSIP 2014 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ChinaSIP.2014.6889342