• DocumentCode
    3541575
  • Title

    Psychovisually-based multiresolution image segmentation

  • Author

    Ramos, Marcia G. ; Hemami, Sheila S. ; Tamburro, Michael A.

  • Author_Institution
    Sch. of Electr. Eng., Cornell Univ., Ithaca, NY, USA
  • Volume
    3
  • fYear
    1997
  • fDate
    26-29 Oct 1997
  • Firstpage
    66
  • Abstract
    Psychophysical studies have shown that there are three image components of distinct perceptual significance to human observers: strong edges, smooth regions, and textured or detailed regions. A psychophysical test was performed to evaluate the perceptual role of each region and a segmentation algorithm was developed to segment an image into the three regions. The segmentation algorithm identifies blocks of an image as belonging to one of the perceptual regions by analyzing high frequency coefficients of a 3-level hierarchical subband/wavelet decomposition. The segmentation algorithm performs well on a wide range of image content, including natural images and mixed images containing text, graphics, and natural scenes
  • Keywords
    image resolution; image segmentation; image texture; visual perception; wavelet transforms; 3-level hierarchical subband/wavelet decomposition; detailed regions; graphics; high frequency coefficients; human observers; image components; image content; mixed images; multiresolution image segmentation; natural images; natural scenes; perceptual regions; psychophysical test; segmentation algorithm; smooth regions; strong edges; text; textured regions; Algorithm design and analysis; Frequency; Humans; Image analysis; Image resolution; Image segmentation; Performance evaluation; Psychology; Testing; Wavelet analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 1997. Proceedings., International Conference on
  • Conference_Location
    Santa Barbara, CA
  • Print_ISBN
    0-8186-8183-7
  • Type

    conf

  • DOI
    10.1109/ICIP.1997.631983
  • Filename
    631983