Edge guided compressive sensing for image reconstruction based on two-stage l 0 minimization
作者: Dan LiZhaojun WuQiang Wang
作者单位: 1College of Astronautics, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, Jiangsu, People’s Republic of China
2Control Science and Engineering, Harbin Institute of Technology, Harbin 150001, Heilongjiang, People’s Republic of China
刊名: Journal of Visual Communication and Image Representation, 2019, Vol.59 , pp.461-474
来源数据库: Elsevier Journal
DOI: 10.1016/j.jvcir.2019.01.025
关键词: Compressive sensingImage reconstructionL 0 minimizationEdge priorMultiple sampling scheme
英文摘要: Abstract(#br)In compressive sensing framework, the results of image reconstruction are sometimes not accurate enough due to the downsampled measurements, especially when the sampling rate is relatively small. This paper proposes a novel edge guided compressive sensing (EGCS) algorithm for natural image reconstruction based on two-stage l 0 minimization, aiming to improve the reconstruction performance. Firstly, wavelet transform is utilized to provide sparsity and multiple sampling scheme is employed to acquire the down-sampled measurements. Then, in the first stage, we design an edge-preserving smoothing method by l 0 gradient minimization to extract the important edge prior accurately, which can not only contribute a lot to improve the reconstruction accuracy of image structures but...
全文获取路径: Elsevier  (合作)

  • minimization 最小化
  • reconstruction 复原
  • Edge 边缘滤器
  • sensing 感觉
  • image 
  • compressive 压缩的
  • based 基于
  • scheme 略图
  • sampling 取样
  • prior 预[优]先