Optimizing Stack Filters by Clone Selection Algorithm

Author

Zhao, Chunhui ; Zhang, Chaozhu ; Ning, Haichun ; Cui, Ying

Author_Institution

Coll. of Inf. & Commun. Eng., Harbin Eng. Univ.

Volume

1

fYear

2006

fDate

16-20 2006

Abstract

The design of stack filters can be formulated as a course of optimizing positive Boolean functions (PBF). In this paper, we use clone selection algorithms (CSA) to optimize stack filters under the mean absolute error (MAE) criterion. The optimal stack filters are used to restore images corrupted with noise. The outcomes are compared with that those optimized by genetic algorithms (GA) and by particle swarm optimization (PSO) Algorithms. Simulation results show that the filters optimized by this method can preserve details well and suppress noise efficiently at the same time. Otherwise, the time spending in computing error cost is much less than that using other two algorithms

Keywords

Boolean functions; genetic algorithms; image denoising; image restoration; particle swarm optimisation; stack filters; clone selection algorithm; genetic algorithms; image restoration; mean absolute error; noise suppression; optimizing stack filters; particle swarm optimization; positive Boolean functions; Boolean functions; Cloning; Computational modeling; Costs; Design optimization; Filters; Genetic algorithms; Image restoration; Optimization methods; Particle swarm optimization;

fLanguage

English

Publisher

ieee

Conference_Titel

Signal Processing, 2006 8th International Conference on

Conference_Location

Beijing

Print_ISBN

0-7803-9736-3

Electronic_ISBN

0-7803-9736-3

Type

conf

DOI

10.1109/ICOSP.2006.344438

Filename

4128774