• DocumentCode
    2577738
  • Title

    Synthesis of 2D and 3D images by generalized long-correlation models

  • Author

    Eom, Kie-Bum ; Park, Juha

  • Author_Institution
    Dept. of Electr. Eng. & Comput. Sci., George Washington Univ., Washington, DC, USA
  • fYear
    1991
  • fDate
    13-16 Oct 1991
  • Firstpage
    253
  • Abstract
    The authors consider the modeling of two-dimensional (2D) and 3D natural scenes by using a single statistical model. A model developed can synthesize both 2D and 3D images that resemble real textures and natural terrains. The new model is a generalization of long-correlation models. The relationship between the new model and fractals is discussed. The performance of generalized long-correlation models is demonstrated by synthesizing various 2D and 3D images resembling real 3D terrains and 2D textures. The authors also present an algorithm for estimating the parameters of generalized long-correlation models. The images generated by estimated parameters look similar to the original images
  • Keywords
    correlation methods; fractals; parameter estimation; picture processing; statistical analysis; 2D images; 2D textures; 3D images; 3D terrains; fractals; image synthesis; long-correlation models; parameter estimation; picture processing; single statistical model; Agricultural engineering; Art; Brownian motion; Fractals; Image analysis; Image generation; Image texture analysis; Parameter estimation; Shape; Time series analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, Man, and Cybernetics, 1991. 'Decision Aiding for Complex Systems, Conference Proceedings., 1991 IEEE International Conference on
  • Conference_Location
    Charlottesville, VA
  • Print_ISBN
    0-7803-0233-8
  • Type

    conf

  • DOI
    10.1109/ICSMC.1991.169694
  • Filename
    169694