Title :
Fuzzy expert system for automatic wavelet shrinkage procedure selection for noise suppression
Author :
Dineva, Adrienn ; Varkonyi-Koczy, Annamaria R. ; Tar, Jozsef K.
Author_Institution :
Doctoral Sch. of Appl., Inf. & Appl. Math., Obuda Univ., Budapest, Hungary
Abstract :
Signal processing is an indispensable issue of several technical areas. Wavelet shrinkage, i.e. thresholding in the wavelet coefficient domain, has been successfully used for signal and image noise removal problems. Although, the selection of the suitable wavelet threshold procedure is still a challenging task, because the applied method has significant impact on the result. Furthermore, the specific choice of wavelet, decomposition level and threshold rule, etc., allows a wide variability of the shrinkage method. This paper presents a new supervisory fuzzy expert system for automatic wavelet shrinkage method selection for noise suppression of unknown signals. Simulation results show efficient performance of the system.
Keywords :
expert systems; fuzzy set theory; image denoising; wavelet transforms; automatic wavelet shrinkage procedure selection; decomposition level; fuzzy expert system; image noise removal problems; noise suppression; signal noise removal problems; signal processing; threshold rule; wavelet coefficient domain; wavelet threshold procedure; Expert systems; Noise measurement; Noise reduction; Signal to noise ratio; Wavelet coefficients;
Conference_Titel :
Intelligent Engineering Systems (INES), 2014 18th International Conference on
Conference_Location :
Tihany
DOI :
10.1109/INES.2014.6909361