• DocumentCode
    933441
  • Title

    Total Variation-Based Image Noise Reduction With Generalized Fidelity Function

  • Author

    Lee, Suk-ho ; Kang, Moon Gi

  • Author_Institution
    Yonsei Univ., Seoul
  • Volume
    14
  • Issue
    11
  • fYear
    2007
  • Firstpage
    832
  • Lastpage
    835
  • Abstract
    In this letter, we analyze the relationship between the change in the intensity value and the scale of an image feature, when a generalized function is used as the fidelity term in the total variation-based noise removal scheme. Based on the analysis, we propose a designing method of the fidelity function that results in any desired monotonic relationship between the intensity change and the scale. As an example, we designed a fidelity function that results in a larger contrast between the intensity change of a small scaled feature and that of a large scaled one than the original total variation-based noise removal scheme that uses the norm as the fidelity function.
  • Keywords
    feature extraction; functions; image denoising; image resolution; image texture; generalized fidelity function; image feature intensity value; image feature scaling; image texture; total variation-based image noise reduction; total variation-based noise removal scheme; Biometrics; Design methodology; Fluid flow measurement; Image analysis; Information technology; Moon; Noise measurement; Noise reduction; Smoothing methods; TV; Fidelity term; noise removal; scale; total variation;
  • fLanguage
    English
  • Journal_Title
    Signal Processing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1070-9908
  • Type

    jour

  • DOI
    10.1109/LSP.2007.901697
  • Filename
    4351953