• DocumentCode
    1604645
  • Title

    Probabilistic Inference to the Problem of Inverse-halftoning based on Statistical Mechanics of Spin Systems

  • Author

    Saika, Yohei ; Inoue, Jun-ichi

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Wakayama Nat. Coll. of Technol.
  • fYear
    2006
  • Firstpage
    4563
  • Lastpage
    4568
  • Abstract
    On the basis of statistical mechanics of spin systems, we formulate the problem of inverse-halftoning using the maximizer of the posterior marginal (MPM) estimate for halftone images which are generated both by the threshold mask method and the clustered-dot dither method. Then, the Monte Carlo simulation for a halftone image clarifies that the MPM estimate works well for inverse-halftoning, if we appropriately set parameters of the Boltzmann factor of the ferromagnetic Q-Ising model used for the model prior. Also, we reveal the result that inverse-halftoning is achieved in inner area of the threshold mask more accurately than on the boundary
  • Keywords
    Monte Carlo methods; image reconstruction; maximum likelihood estimation; probability; spin systems; statistical mechanics; Boltzmann factor; Monte Carlo simulation; clustered-dot dither method; ferromagnetic Q-Ising model; image halftone; inverse-halftoning problem; maximizer of the posterior marginal estimation; probabilistic inference; spin system; statistical mechanics; threshold mask method; Clustering algorithms; Educational institutions; Facsimile; Filters; Glass; Image generation; Information processing; Information science; Pixel; Printing; inverse-halftoning; statistical mechanics; the maximizer of the posterior marginal estimate;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    SICE-ICASE, 2006. International Joint Conference
  • Conference_Location
    Busan
  • Print_ISBN
    89-950038-4-7
  • Electronic_ISBN
    89-950038-5-5
  • Type

    conf

  • DOI
    10.1109/SICE.2006.315089
  • Filename
    4108482