Title :
SNR optimisation using genetic algorithm
Author :
Suthaharan, Shan ; Zhang, Zhongwei
Author_Institution :
Sch. of Comput. & Inf. Technol., Monash Univ., Clayton, Vic., Australia
Abstract :
A new technique based a genetic algorithm is proposed in this paper to find the optimal value of the ratio Γ, which is a priori knowledge of the signal-to-noise ratio, in the Wiener filter for image restoration. The proposed method can be used in a control experiment in conjunction with any image-quality-assessment measure in order to obtain the optimal Γ for the measure. In the control experiment, the minimum mean square error (MSE) and image activity weighted error (IAWE) are used
Keywords :
Wiener filters; genetic algorithms; image restoration; interference suppression; least mean squares methods; SNR optimisation; Wiener filter; a priori knowledge; genetic algorithm; image activity weighted error; image restoration; image-quality-assessment measure; minimum mean square error; signal-to-noise ratio; Degradation; Equations; Fourier transforms; Genetic algorithms; Image restoration; Layout; Mean square error methods; Pixel; Signal to noise ratio; Wiener filter;
Conference_Titel :
Image Processing, 1997. Proceedings., International Conference on
Conference_Location :
Santa Barbara, CA
Print_ISBN :
0-8186-8183-7
DOI :
10.1109/ICIP.1997.647763
