• DocumentCode
    1622868
  • Title

    Image contrast enhancement based on a local standard deviation model

  • Author

    Chang, Dah-chung ; Wu, Wen-Rong

  • Author_Institution
    Dept. of Commun. Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan
  • Volume
    3
  • fYear
    1996
  • Firstpage
    1826
  • Abstract
    The adaptive contrast enhancement (ACE) algorithm is a widely used image enhancement method, which needs a contrast gain to adjust high frequency components of an image. In the literature, the gain is usually inversely proportional to the local standard deviation (LSD) or is a constant. But these cause two problems in practical applications, i.e., noise overenhancement and ringing artifact. Here, a new gain is developed based on Hunt´s (1976) Gaussian image model to prevent the two defects. The new gain is a nonlinear function of LSD and has the desired characteristic emphasizing the LSD regions in which details are concentrated. The authors have applied the new ACE algorithm to chest X-ray images and the simulations show the effectiveness of the proposed algorithm
  • Keywords
    adaptive signal processing; diagnostic radiography; image enhancement; medical image processing; modelling; Hunt´s Gaussian image model; adaptive contrast enhancement algorithm; chest X-ray images; image contrast enhancement; image high frequency components; local standard deviation model; medical diagnostic imaging; noise overenhancement; nonlinear function; ringing artifact; Adaptive equalizers; Biomedical equipment; Communication standards; Frequency; Histograms; Image enhancement; Medical services; Medical simulation; Noise reduction; X-ray imaging;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Nuclear Science Symposium, 1996. Conference Record., 1996 IEEE
  • Conference_Location
    Anaheim, CA
  • ISSN
    1082-3654
  • Print_ISBN
    0-7803-3534-1
  • Type

    conf

  • DOI
    10.1109/NSSMIC.1996.587984
  • Filename
    587984