A relaxation evolutionary image restoration method

Author

Wang, Zhe ; Yu, Yinglin

Author_Institution

Res. Inst. of Radio & Autom., South China Univ. of Technol., Guangzhou, China

Volume

2

fYear

1997

fDate

12-15 Oct 1997

Firstpage

1100

Abstract

Evolution strategies (ESs) are global optimization models in the light of natural evolution. Using relaxation evolution strategy, a novel method for restoration of gray level images blurred by a known shift-invariant point spread function and corrupted by added Gaussian white noise is presented in this paper. With relaxation mutation and other improvements of traditional ESs, a practical evolution image restoration method is proposed. Computer simulation examples illustrate the usefulness of our method. Comparisons to other image restoration methods, such as inverse filter and neural restoration method, are also provided

Keywords

Gaussian noise; genetic algorithms; image restoration; iterative methods; optical transfer function; relaxation theory; search problems; white noise; Gaussian white noise; global optimization models; gray level images; image restoration; iterative method; relaxation evolutionary; relaxation mutation; search space; shift-invariant point spread function; Automation; Computer simulation; Degradation; Electronic switching systems; Fault tolerance; Genetic mutations; Hopfield neural networks; Image converters; Image restoration; White noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on

Conference_Location

Orlando, FL

ISSN

1062-922X

Print_ISBN

0-7803-4053-1

Type

conf

DOI

10.1109/ICSMC.1997.638096

Filename

638096