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Noise reduction and image sharpening using IJA stochastic learning automaton

Nooraliei, A ; Sharif University of Technology | 2010

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  1. Type of Document: Article
  2. DOI: 10.1109/ICCRD.2010.175
  3. Publisher: 2010
  4. Abstract:
  5. This paper utilizes IJA stochastic learning automaton for detecting noise and tuning value of alpha parameter which is used for image sharpening via gas diffusion model. The method has been applied to gray-scale images in an automatic and adaptive fashion. It is shown that the IJA automaton detects noise and can reform it appropriately. It glides the image to find the pattern of noise and replace it by the relevant characteristics of neighborhood to carry out the local restoration. Then, the automaton makes the image sharp with gas diffusion model by learning alpha parameter. The IJA automaton calculates appropriate local value for each pixel. Finally, experiments are presented and comparisons with other common used techniques are introduced which illustrate the proposed approach produces excellent results for the problem of restoring gray-scale images
  6. Keywords:
  7. Gas deffusion model ; IJA automata ; Image sharpenning ; Alpha parameters ; Gas diffusion ; Gray-scale images ; Image sharpenning ; Noise reductions ; Stochastic learning automata ; Acoustic noise measurement ; Automata theory ; Diffusion in gases ; Robots ; Stochastic models ; Stochastic systems ; Translation (languages)
  8. Source: 2nd International Conference on Computer Research and Development, ICCRD 2010, 7 May 2010 through 10 May 2010 ; May , 2010 , Pages 790-794 ; 9780769540436 (ISBN)
  9. URL: http://ieeexplore.ieee.org/document/5489491/?reload=true