Image Restoration by Using Evolutionary Technique to Denoise Gaussian and Impulse Noise

  • Nallaperumal Krishnan
  • Subramanyam Muthukumar
  • Subban Ravi
  • D. Shashikala
  • P. Pasupathi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8284)


Most of the techniques for image restoration are based on some known degradation models. Here a genetic algorithm based filter is used to restore the degraded image without having any prior knowledge about the blurring model or noise type. The observed degraded image is denoised and the initial target image is generated by blind deconvolution technique using higher-order statistics. Recombination and mutation mechanisms are implemented to create better individuals. More good solutions are generated by the selection of fittest individuals. The selection procedure is based on the similarity of the individuals with the target image. In this method, the initial target image is obtained by significantly removing noise with both Gaussian and non-Gaussian probability distributions, hence the convergence of the solution set becomes faster.


Blind Deconvolution Color Image Restoration Higher Order Statistics 


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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Nallaperumal Krishnan
    • 1
  • Subramanyam Muthukumar
    • 1
  • Subban Ravi
    • 2
  • D. Shashikala
    • 2
  • P. Pasupathi
    • 2
  1. 1.Centre for IT and Engg.Manonmaniam Sundaranar UniversityTirunelveliIndia
  2. 2.Dept. of Computer SciencePondicherry UniversityPondicherryIndia

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