• DocumentCode
    1851290
  • Title

    Intensity-Preserving Contrast Enhancement for Gray-Level Images using Multi-objective Particle Swarm Optimization

  • Author

    Kwok, N.M. ; Ha, Q.P. ; Liu, D.K. ; Fang, G.

  • Author_Institution
    ARC Centre of Excellence for Autonomous Syst., Univ. of Technol., Sydney, NSW
  • fYear
    2006
  • fDate
    8-10 Oct. 2006
  • Firstpage
    21
  • Lastpage
    26
  • Abstract
    This paper addresses the enhancement of the contrast of gray-level digital images while preserving the mean image intensity, thus, providing better viewing consistency and effectiveness. The contrast enhancement is achieved by maximizing the information content carried in the image with a continuous intensity transform function and the mean image intensity is preserved, by using the gamma-correction approach. Since the contrast enhancement and intensity preservation are contradicting, a multi-objective particle swarm optimization (MPSO) algorithm is developed to resolve this trade-off. Benchmark images, street senses and skyline images are included to illustrate the effectiveness of the proposed approach
  • Keywords
    computer vision; image enhancement; particle swarm optimisation; benchmark images; continuous intensity transform function; digital images; gamma correction; gray-level images; intensity-preserving contrast enhancement; mean image intensity; multi-objective particle swarm optimization; skyline images; street senses; Australia; Automation; Biomedical engineering; Content addressable storage; Digital images; Histograms; Image processing; Optimization methods; Particle swarm optimization; Pixel;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Automation Science and Engineering, 2006. CASE '06. IEEE International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    1-4244-0310-3
  • Electronic_ISBN
    1-4244-0311-1
  • Type

    conf

  • DOI
    10.1109/COASE.2006.326849
  • Filename
    4120315