Tree structure sparsity pattern guided convex optimization for compressive sensing of large-scale images

Wei Jie Liang, Gang Xuan Lin, Chun Shien Lu

研究成果: Article同行評審

4 引文 斯高帕斯(Scopus)

摘要

Cost-efficient compressive sensing of large-scale images with quickly reconstructed high-quality results is very challenging. In this paper, we present an algorithm to solve convex optimization via the tree structure sparsity pattern, which can be run in the operator to reduce computation cost and maintain good quality, especially for large-scale images. We also provide convergence analysis and convergence rate analysis for the proposed method. The feasibility of our method is verified through simulations and comparison with the state-of-the-art algorithms.

原文English
文章編號7762896
頁(從 - 到)847-859
頁數13
期刊IEEE Transactions on Image Processing
26
發行號2
DOIs
出版狀態Published - 2017 二月

All Science Journal Classification (ASJC) codes

  • 軟體
  • 電腦繪圖與電腦輔助設計

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