350 rub
Journal Neurocomputers №8 for 2013 г.
Article in number:
Intellectual image noise reduction algorithm
Authors:
S.N. Zagoruyko, P.V. Skribtsov
Abstract:
New intellectual image noise reduction algorithm based on Markov networks is announced. For states generation linear and neural models are used. For state probability estimation binomial distribution is used. Announced algorithm is able to perform image noise reduction preserving details.
Pages: 38-41
References

  1. Freeman W. T., Jones T. R., and Pasztor E. C. Example-based super-resolution. IEEE Computer Graphics and Applications. 2002. V. 22. № 2. R. 56-65.
  2. Celis M., Dennis J. E., and Tapia R. A. A trust region strategy for nonlinear equality constrained optimization. Numerical Optimization, 1984. (P. Boggs, R. Byrd and R. Schnabel, eds), Philadelphia: SIAM. 1985. R. 71-82.