Abstract
When a linear mixture of independent sources is contaminated by multiplicative noise, also called speckle noise, the statistic of the outputs of a linear transformation of the noise data is very different from the statistic that appears when the speckle noise is not present. Specifically, it is not possible find a linear transformation that provides independent outputs and it is necessary study the statistical structure that appears in this case. In this paper, a general approach to obtain the mixture when there exists speckle noise is developed. In order to do this, the linear transformation is searches as the one that reproduces the this theoretical statistic structure.
Acknowledgements: This work was partially supported by the “Ministerio de Ciencia y Tecnología” of Spain under Project TIC 2001-2902.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bell, A.J., Sejnowski, T.J.: Edges are the independent components of natural scenes. Advances in Neural Information Processing Systems 9, 831–837 (1997)
Blanco, D., Mulgrew, B., McLaughlin, S.: ICA method for speckle signals. In: Proc. of ICASSP (2004)
Chiang, S.S., CHang, C.I., Ginsberg, I.W.: Unsupervised target detection in hyperspectral images using projection pursuit. IEEE Trans. on Geos. and Tem. Sens. 39, 1380–1391 (2001)
Chitroub, S., Sansal, B.: Statistical characterisation and modelling of SAR images. Signal Processing 82, 69–92 (2002)
Chitroub, S., Sansal, B.: Unsupervised learning rules for POLISAR images analysis. In: Proc. of NNSP, pp. 567–576 (2002)
Karvonen, J., Similä, M.: Independent component analysis for ice SAR image classification. In: Proc. of IGARSS, pp. 1255–1257 (2001)
Lennon, M., Mercier, G., Mouchot, M.C., Hubert-Moy, L.: Independent component analysis as a tool for the dimensionality reduction and the representation of hyperspectral images. In: Proc. of IGARSS, pp. 2893–2895 (2001)
Neemuchwala, H., Hero, A., Carson, P.: Image registration using entropic graphmathching criteria. In: Proc. of Asilomar Conf. on Signal and Sistem (2002)
Zhang, X., Chen, C.H.: A new independent component analyis (ICA) method and its application to SAR images. In: Proc. of NNSP, pp. 283–292 (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2004 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Blanco, D., Mulgrew, B., McLaughlin, S., Ruiz, D.P., Carrion, M.C. (2004). The Use of ICA in Speckle Noise. In: Puntonet, C.G., Prieto, A. (eds) Independent Component Analysis and Blind Signal Separation. ICA 2004. Lecture Notes in Computer Science, vol 3195. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30110-3_32
Download citation
DOI: https://doi.org/10.1007/978-3-540-30110-3_32
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23056-4
Online ISBN: 978-3-540-30110-3
eBook Packages: Springer Book Archive