The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing 2008
996
Chitroub, S., Houacine, A. and Sansal, B., 2004. PCA-ICA
neural network model for POLSAR images analysis. In
Proceedings of IEEE International Conference on Acoustic,
Speech, and Signal Processing (ICASSP’04), Montreal, Canada.
Vol. V, pp. 757-760.
S. Chitroub, 2006. Two ICA Approaches for SAR Image
Enhancement Part II: Independent Component Analysis of
POLarimetric Synthetic Aperture Radar (POLSAR) Images.
Bayesian Approach. Signal and Image Processing for Remote
Sensing”, Edited by Prof. C.H. Chen, University of
Massachusetts Dartmouth, Publisher: Taylor & Francis, CRC
Pressm pp. 655-675.
Frank, M. and Menz, G., 2003. Detecting Seasonal Cseasonal
changes in a semi-arid environment using hyperspectral
vegetation indices. Presented at the 3 rd EARSel Workshop on
Imageing Spectroscopy, Herrsching.
Gracia, M. and Ustin, S. L., 2001. Detection of interannual
vegetation responses to climatic variablity using AVIRIS data
in a coastal savanna in California. IEEE Transactions on
Geoscience and Remote Sensing, 39(7), pp. 1480-1490.
Hyvarinen, A., 1999. Fast and robust fixed-point algorithms for
independent component analysis. IEEE Transactions on Neural
Networks, 10(3), pp. 626-634.
Karhunen, J. and Joutsensalo, J., 1994. Representation and
separation of signals using nonlinear PC A type learning. Neural
Networks, 7, pp. 113-127.
Kogan, N., Gitelson, A., Edige, Z., Spivak I., and Lebed, L.,
2003. AVHRR-based spectral vegetation index for quantitative
assessment of vegetation state and productivity: Calibration and
validation. Photogrammetric Engineering and Remote Sensing,
69(8), pp. 899-906.
Lee, T. W., Girolami, M., and Sejnowski, T. J. , 1999.
Independent component analysis using an extended infomax
algorithm for mixed subgaussian and supergaussian sources.
Neural Computation, 11, pp. 417-441.
Lee, T. W., Girolami, M., Bell, A. J. and Sejnowski, T. J., 2000.
A Unifying information-theoretic framework for independent
component analysis, Neural Networks, 39, pp. 1-21.
Shabanov, N. V., Zhou, L., Knyazikhin, Y., Ranga, B. and
Tucker, C. J., 2001. Analysis of interannual changes in northern
vegetation activity observed in AVHRR data from 1981 to 1994.
IEEE Transactions on Geoscience and Remote Sensing, 39(7),
pp. 1480-1490.
Figure 1. PCA-ICA neural network model
wi Ci w 2 Cz
Figure 2. PCA-based part of the model