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Neural Evolution Model for Gray Level Image Restoration

  • David Zhang
  • Xiaobo Li
  • Zhiyong Liu
Part of the The International Series on Asian Studies in Computer and Information Science book series (ASIS, volume 11)

Abstract

This chapter introduces a novel image restoration method by using modified evolution strategy (MES). We first review the background of image restoration and some useful concepts associated with it. A MSE image restoration model is made in Section 4.2. Three main improvements that consist of coordinate descending mutation, “survival of the fittest” selection rule and hybrid evolution strategies are presented in Section 4.3. Neural evolution algorithm is introduced in Section 4.4. Theoretical analysis and experimental results in Section 4.5 demonstrate the efficiency of the proposed method. In Section 4.6, we draw a conclusion.

Keywords

Image Restoration Gray Level Image Degraded Image Evolution Strategy Hopfield Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 2001

Authors and Affiliations

  • David Zhang
    • 1
  • Xiaobo Li
    • 2
  • Zhiyong Liu
    • 3
  1. 1.Hong Kong Polytechnic UniversityHong Kong
  2. 2.University of AlbertaCanada
  3. 3.National Natural Science Foundation of ChinaChina

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