• DocumentCode
    2000510
  • Title

    Green noise digital halftoning

  • Author

    Lau, Daniel Leo ; Arce, Gonzalo R. ; Gallagher, Neal C.

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Delaware Univ., Newark, DE, USA
  • Volume
    2
  • fYear
    1998
  • fDate
    4-7 Oct 1998
  • Firstpage
    39
  • Abstract
    We introduce the concept of green noise-the mid-frequency component of white noise-and its advantages over blue noise for digital halftoning. Unlike blue noise, which creates the illusion of continuous tone by spreading the minority pixels of a binary dither pattern as homogeneously as possible, green noise forms minority pixel clusters which are themselves distributed as homogeneously as possible. By clustering pixels, green noise patterns are less susceptible to image degradation from printer distortions such as dot-overlap (the overlapping of a printed dot with its nearest neighbors), and by adjusting the average number of pixels per cluster, green noise patterns are tunable to specific printer characteristics. Using both spectral and spatial statistics, are establish models for ideal green noise patterns
  • Keywords
    noise; pattern clustering; printers; spectral analysis; statistical analysis; binary dither pattern; blue noise; continuous tone; digital halftoning; dot-overlap; green noise patterns; image degradation; mid-frequency component; minority pixel clusters; printer characteristics; printer distortions; spatial statistics; spectral statistics; white noise; Amplitude modulation; Degradation; Frequency modulation; Internet; Nearest neighbor searches; Pixel; Printers; Statistical analysis; Statistics; Stochastic processes;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image Processing, 1998. ICIP 98. Proceedings. 1998 International Conference on
  • Conference_Location
    Chicago, IL
  • Print_ISBN
    0-8186-8821-1
  • Type

    conf

  • DOI
    10.1109/ICIP.1998.723313
  • Filename
    723313