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
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