Compressive large-scale image sensing

Wei-Jie Liang, Gang Xuan Lin, Chun Shien Lu

研究成果: Conference contribution

摘要

Cost-efficient compressive sensing of large-scale images with fast reconstructed high-quality results is very challenging. In this paper, we propose a new compressive large-scale image sensing method, composed of operator-based strategy in the context of fixed point continuation technique and weighted LASSO with tree structure sparsity pattern. The main characteristic of our method is free from any assumptions and restrictions. The feasibility of our method is verified via computational complexity and convergence analyses, extensive simulations, and comparisons with state-of-the-art algorithms.

原文English
主出版物標題2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015
發行者Institute of Electrical and Electronics Engineers Inc.
頁面378-382
頁數5
ISBN(電子)9781479975914
DOIs
出版狀態Published - 2016 二月 23
事件IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015 - Orlando, United States
持續時間: 2015 十二月 132015 十二月 16

出版系列

名字2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015

Other

OtherIEEE Global Conference on Signal and Information Processing, GlobalSIP 2015
國家United States
城市Orlando
期間15-12-1315-12-16

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Signal Processing

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  • 引用此

    Liang, W-J., Lin, G. X., & Lu, C. S. (2016). Compressive large-scale image sensing. 於 2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015 (頁 378-382). [7418221] (2015 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GlobalSIP.2015.7418221