A comparison of PCA/ICA for data preprocessing in remote sensing imagery classification

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 6044, Issue , 2005, Pages

  He, Hui ^a   Yu, Xianchuan ^a  

^a BEIJING NORMAL UNIVERSITY   (China)

Author keywords

Data mining; EFFICA; Fast ICA; Kernel ICA; Maximum Likelihood Classification; Principle component Analysis; Remote Sensing Imagery

Indexed keywords

ALGORITHMS; DATA MINING; DATA PROCESSING; IMAGE SEGMENTATION; INDEPENDENT COMPONENT ANALYSIS; MAXIMUM LIKELIHOOD ESTIMATION; REMOTE SENSING;

EFFICA; FAST-ICA; KERNEL-ICA; REMOTE SENSING IMAGERY;

PRINCIPAL COMPONENT ANALYSIS;

EID: 33645019430     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.652298     Document Type: Conference Paper

References (20)

1. H. Szu, LiMing Zhang. Pattern process of the intellectual vision: The unsupervising learning and other methods applied to image of multicenter. Shanghai: The publishing house of the education of science and technology of Shanghai, 2002(in Chinese)
2. Shenggen Zeng, Xiaomin Wang, et al.. Technology of remote sensing image classification based on independent component analysis. Remote sensing journal, 8(2),pp: 150-158,2004 (in Chinese)
3. Shah, C. A., Watanachaturaporn, P., Arora, M. K., and Varshney, P. K. Some Recent Results on Hyperspectral Image Classification. In IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data, NASA Goddard Spaceflight center, Greenbelt, MD,October 27-28, 2003
4. Xianchuan YU, Xiaochun Cheng et al. Research of independent component analysis,IEEE International Conference On Systems, Man, And Cybernatics, Conference Proceedings, Vols 1-7: 4804-4809, (Oct.10-13, Hague, Netherlands), ISBN: 0-7803-8566-7, 2004
5. Jutten and J. Herault. Blind separation of sources, part I: An adaptive algorithm based on neuromimetic architecture. Signal Processing, 24: 1-10,1991
6. P. Comon.Independent component analysis, a new concept? Signal Processing, 36(3):287-314,1994
7. A. J. Bell, T. J. Sejnowski. An information-maximization approach to blind separation and blind deconvolution. Neural Computation, 7(6):1129-1159,1995
8. J. -F. Cardoso. High-order contrasts for independent component analysis. In Proc. ICASSP, 1998
9. A. Hyvärinen, J. Karhunen, E. Oja. Independent Component Analysis. John Wiley& Sons, 2001
10. Bach, F.R., Jordan, M.I. Finding clusters in independent component analysis. In: 4th Intl. Symp. on Independent Component Analysis and Signal Separation (ICA2003), Nara, Japan, 2003
11. Naoko Kosaka and Yukio Kosugi: ICA Aided Linear Spectral Mixture Analysis of Agricultural Remote Sensing Images. Proc. Fourth International Symposium on Independent Component Analysis and Blind Signal Separation, pp.221-226, 2003
12. Hongtao Du, Hairong Qi, Xiaoling Wang, Rajeev Ramanath, Wesley E. Snyder: Band Selection Using Independent Component Analysis for Hyperspectral Image Processing. AIPR: 93-98, 2003
13. Chintan A. Shah, Ph.D. Student. Advanced Land Cover Mapping and Change Detection Techniques, Electrical Engineering and Computer Science Department, Syracuse University, 2003
14. Aapo Hyvarinen. Fast and Robust Fixed-Point Algorithms for Independent Component Analysis, IEEE Transactions, 10(3):4-7,1999
15. Hyvarinen A. "The Fixed-point Algorithm and maximum likelihood estimation for Independent Component Analysis",Neural Processing Letters, 10(1):1-8, 2000
16. Mitianoudis, N., Davies, M.E. New fixed-point solutions for convolved mixtures. In: 3rd Intl. Conf. on Independent Component Analysis and Source Separation (ICA2001), San Diego, California, 2001
17. F. R. Bach and M. I. Jordan. Kernel independent component analysis. J. of Machine Learning Research, 3:1-48, 2002
18. Lee T.Independent Component Analysis: Theory and Application. Kluwer Academic Publishers, 1998
19. Aiyou Chen, Peter Bickel, Efficient Independent Component Analysis (I). Department of Statistics University of California Berkeley, CA 94720, USA
20. Bach, F.R., Jordan, M.I. Kernel independent component analysis. Technical Report UCB/CSD-01-1166, Division of Computer Science, University of California, Berkeley, 2001