• DocumentCode
    237661
  • Title

    Training cellular automata for salt and pepper noise filtering

  • Author

    Shukla, Anand Prakash ; Agarwal, Sankalp

  • Author_Institution
    Dept. of Comput. Sci. & Eng., Motilal Nehru Nat. Inst. of Technol., Allahabad, India
  • fYear
    2014
  • fDate
    28-29 Nov. 2014
  • Firstpage
    519
  • Lastpage
    524
  • Abstract
    Cellular Automata is significantly applying to image processing operations. The description about the use of training of cellular automata for filtering the salt and pepper noise in binary images is exemplified in this paper. The selection of the best rule set from large search space has been performed on the basis of sequential floating forward search method. The peak signal to noise ratio values between original and filtered image is used as the objective function. The proposed method is also compared with some standard methods and found to perform better in respect to restoration of the image.
  • Keywords
    cellular automata; image denoising; image filtering; image restoration; search problems; best rule set; binary images; cellular automata training; filtered image; image processing operations; image restoration; peak signal to noise ratio values; salt and pepper noise filtering; sequential floating forward search method; Automata; Biological system modeling; Image processing; Learning automata; PSNR; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence on Power, Energy and Controls with their impact on Humanity (CIPECH), 2014 Innovative Applications of
  • Conference_Location
    Ghaziabad
  • Type

    conf

  • DOI
    10.1109/CIPECH.2014.7019128
  • Filename
    7019128