DocumentCode :
2930498
Title :
Using Fuzzy Logic and Particle Swarm Optimization to design an image filter
Author :
Hung-Hsu Tsai ; Bae-Muu Chang ; Ji-Shiang Shih ; Ji-Shiang Shih
Author_Institution :
Dept. of Inf. Manage., Nat. Formosa Univ., Hu-Wei, Taiwan
fYear :
2012
fDate :
16-18 Nov. 2012
Firstpage :
72
Lastpage :
77
Abstract :
This paper presents an Image Filter with noise detector using Fuzzy Logic and Particle Swarm Optimization (PSO), which is called the IFFLPSO filter, for removal and restoration of impulse noises. In IFFLPSO filter, the fuzzy logic is employed to efficiently design the noise detector. The proposed filter effectively judges the input pixel vector whether it is corrupted or not. Meanwhile, the particle swarm optimization algorithm (PSO) is utilized so as to optimize the noise detectors to enhance the noise detection performance. Subsequently, in order to enhance the restoration performance of proposed filter, the color ratio of spot´s region in the restored image is employed to determine the spot´s color. Also, the pixel vectors with different color ratios in the spot region are detected. Finally, the vector median filter is utilized to restore the corrupted pixels. Experimental results demonstrate that the proposed image filter outperforms the existing other well-known filters in restoration performance. And the system can be widely applied in microarray image processing.
Keywords :
fuzzy logic; image colour analysis; image denoising; image enhancement; image restoration; median filters; particle swarm optimisation; IFFLPSO filter; PSO; fuzzy logic; image filter design; impulse noise detection; impulse noise restoration; microarray image processing; noise detector; particle swarm optimization; pixel vector; spot region color ratio; vector median filter; Filtering algorithms; Filtering theory; Image color analysis; Image restoration; Noise; Training; Vectors; color image filter; fuzzy logic; image restoration; microarray image processing; noise reduction; particle swarm optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Theory and it's Applications (iFUZZY), 2012 International Conference on
Conference_Location :
Taichung
Print_ISBN :
978-1-4673-2057-3
Type :
conf
DOI :
10.1109/iFUZZY.2012.6409678
Filename :
6409678
Link To Document :
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