DocumentCode :
436481
Title :
Application of independent component analysis on noisy image separation
Author :
Zhao, Hao ; Zhou, Weidong ; Peng, Yuhua
Author_Institution :
Sch. of Inf. Sci. & Eng., Shandong Univ., Jinan, China
Volume :
2
fYear :
2004
fDate :
31 Aug.-4 Sept. 2004
Firstpage :
1018
Abstract :
The basic model and methods of independent component analysis (ICA) are introduced in this paper. The ICA of noisy signals is discussed. The technique of wavelet threshold denoising and the algorithm of FastICA are both studied with computer simulation of noisy image separation. The simulation results show that for the mixed images with additive white Gaussian noise, it´s better to denoise the images before applying ICA than to apply ICA first and then denoise the independent components.
Keywords :
AWGN; blind source separation; image denoising; independent component analysis; wavelet transforms; additive white Gaussian noise; fastICA algorithm; independent component analysis; noisy image separation; wavelet threshold denoising; Data analysis; Independent component analysis; Large Hadron Collider; Noise reduction; Principal component analysis; Signal processing; Signal processing algorithms; Statistics; Wavelet analysis; Wavelet domain;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing, 2004. Proceedings. ICSP '04. 2004 7th International Conference on
Print_ISBN :
0-7803-8406-7
Type :
conf
DOI :
10.1109/ICOSP.2004.1441494
Filename :
1441494
Link To Document :
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