Cleaning Scattered Multi-Channel Data

Ronell Carey; Maurice Craig

doi:10.1071/EG04131

ISSN: 0812-3985
E-ISSN: 1834-7533

Cleaning Scattered Multi-Channel Data
Authors Ronell Carey and Maurice Craig
Publisher: Australian Society of Exploration Geophysicists
Source: Exploration Geophysics, Volume 35, Issue 2, Jun 2004, p. 131 - 136
DOI: https://doi.org/10.1071/EG04131
- Received: 30 Mar 2004
- Published online: 01 Jun 2004

Abstract

A new type of “maximum noise fraction” transform, for multivariate data, facilitates noise reduction without requiring the samples to vary continuously, and without need to collect “noise” statistics. The algorithm specifically targets data with a hundred or more channels. Its main applications will be to hyper-spectral remote sensing data and to airborne gamma-ray spectrometry.

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References

Castleman, K.R., 1979, Digital Image Processing: Prentice-Hall, Inc.
Dickson, B., and Taylor, G., 2000, Maximum noise fraction method reveals detail in aerial gamma-ray surveys: Exploration Geophysics, 31, 73-77.
Green, A., Berman, M., Switzer, P., and Craig, M., 1988, A transformation for ordering multispectral data in terms of image quality with implications for noise removal: IEEE Transactions on Geoscience and Remote Sensing, 26, 65-74.
Lee, J.B., Woodyatt, S., and Berman, M., 1990, Enhancement of high spectral resolution remote-sensing data by a noise-adjusted principal components transform: IEEE Transactions on Geoscience and Remote Sensing, 28, 295-304.
Pendock, N., 1994, Multispectral image enhancement using a neural network and the maximum noise fraction transform: Proceedings of the Seventh Australasian Remote Sensing Conference, 415-122.
Press, W.H., Flannery, B.P, Teukolsky, S.A., and Vetterling, W.T., 1992, Numerical Recipes in C (2nd ed). Cambridge University Press.
Taussky, O., 1949, A recurring theorem on determinants: American Mathematical Monthly, 56, 672-676.

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Article Type: Research Article

Keyword(s): Hyper-spectral; Maximum noise fraction; Multivariate data; Principal components transform

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Cleaning Scattered Multi-Channel Data

Abstract

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