Geometric structure based intelligent collaborative compressive sensing for image reconstruction by l 0 minimization
作者: Dan LiQiang WangYi Shen
作者单位: 1Control Science and Engineering, Harbin Institute of Technology, No.92, West Da-Zhi Street, Nangang District, Harbin 150001, China
刊名: Neurocomputing, 2017, Vol.260 , pp.221-234
来源数据库: Elsevier Journal
DOI: 10.1016/j.neucom.2017.04.035
关键词: Image reconstructionL 0 minimizationGeometric structureNonlocal self-similarityPrior informationIntelligent searching
原始语种摘要: Abstract(#br)Image reconstruction by l 0 minimization is an NP-hard problem with high computational complexity and the results are sometimes not accurate enough due to the down-sampled measurements. In this paper, we propose a novel geometric structure based intelligent collaborative compressive sensing (G-ICCS) method for image reconstruction by l 0 minimization. Firstly, the local geometric structures of image are exploited to establish the geometric structure based sparsity models based on the geometric over-completed dictionaries, which aims to enhance the reconstruction accuracy of image structures. To reduce the computational complexity and achieve the better reconstruction accuracy, we utilize the nonlocal self-similarity property to obtain the geometric sparsity prior to guide the...
全文获取路径: Elsevier  (合作)
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影响因子:1.634 (2012)

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关键词翻译
关键词翻译
  • reconstruction 复原
  • minimization 最小化
  • intelligent 有理性的
  • image 
  • geometric 凡何
  • collaborative 合作的
  • searching 勘探
  • sensing 感觉
  • computational 计算的
  • structure 构造