• DocumentCode
    677280
  • Title

    Image decomposition model combined with sparse representation and total variation

  • Author

    Xuan Zhu ; Ning Wang ; Enbiao Lin ; Qiuju Li ; Xufeng Zhang

  • Author_Institution
    Sch. of Inf. Sci. & Technol., Northwest Univ., Xi´an, China
  • fYear
    2013
  • fDate
    26-28 Aug. 2013
  • Firstpage
    86
  • Lastpage
    91
  • Abstract
    In this paper, we propose a new decomposition model combined with sparse representation and total variation (SRTV), which allows us to separate cartoon and texture components from an image. The SRTV model naturally fits into the framework of separation and produces separated layers, meanwhile, denoising and inpainting process appears as the byproducts. Therefore, the new approach incorporates separation, denoising, and inpainting as a unified framework. We demonstrate the performance of the new approach through several examples.
  • Keywords
    image denoising; image representation; image segmentation; image texture; SRTV; cartoon; denoising process; image decomposition model; inpainting process; separation; sparse representation; texture component; total variation; Analytical models; Dictionaries; Image decomposition; Mathematical model; Noise reduction; Optimized production technology; Transforms; Total variation; decomposition; denosing; inpainting; sparse representation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Automation (ICIA), 2013 IEEE International Conference on
  • Conference_Location
    Yinchuan
  • Type

    conf

  • DOI
    10.1109/ICInfA.2013.6720275
  • Filename
    6720275