Noise reduction of aerial gamma-ray surveys

Bruce Dickson; Geoffrey Taylor

doi:10.1071/EG998324

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

Noise reduction of aerial gamma-ray surveys
Authors Bruce Dickson^a and Geoffrey Taylor^b
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^a CSIRO Exploration & Mining, , PO Box 136, North Ryde, , NSW 2113, . Phone: (02) 9490 8767, Fax: (02) 9490 8921, Email: B.Dickson @syd.dem.csiro.au ^b Pitt Research, , Hackney, , SA 5069, . Phone: (08) 8362 9966, Fax: (08) 8362 9977
Publisher: Australian Society of Exploration Geophysicists
Source: Exploration Geophysics, Volume 29, Issue 3-4, Sep 1998, p. 324 - 329
DOI: https://doi.org/10.1071/EG998324
- Published online: 01 Sep 1998

Abstract

Two methods of reducing noise in aerial survey data have been evaluated as to their performance on a set of spectra measured with a laboratory spectrometer and a section of an aerial survey. The two methods were Noise Adjusted Singular Value Decomposition (NASVD) and Maximum Noise Fraction (MNF). These are applied to the spectral data before subsequent processing to determine potassium, uranium and thorium concentrations. The MNF method was found most effective at removing noise from U and Th signals, reducing noise in U by a factor of 3.5 and Th by 1.5. No technique investigated gave an effective noise reduction for K. The MNF technique requires that a measure of the noise be obtained and this is best done using the differences of adjoining spectra along flight lines. Parameters such as the number of spectral channels to use in the analysis and the number of MNF components to retain in reconstructing the smoothed spectra were investigated. We recommend keeping around 40 MNF components to ensure minor spatially related signal is retained and using spectral data in the range 200 to 3000 keV.

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References

Briggs, I.C., 1974. Machine contouring using minimum curvature. Geophysics, 39, 39–48.
Bristow, Q., 1983, Airborne gamma-ray spectrometry in uranium exploration. Principles and current practice: Internat. J. Appl. Radiation Isotopes, 34,199–229.
Darnley, A.G., 1977, The advantages of standardizing radiometric exploration measurements, and how to do it: Can. Inst. Mining Bull., Feb, 91–95.
Grasty, R.L., Glynn, J.E. and Grant, J.A., 1985, The analysis of multichannel airborne gamma-ray spectra: Geophysics, 50, 2611–2620.
Grasty, R.L., 1982, Utilizing experimentally derived multi-channel gamma-ray spectra for the analysis of airborne data: in Proc. Uranium Exploration Methods. Review of NEA; IAEA R&D Programme, OECD Nuclear Energy Agency, 653–668.
Green, A.A., Berman, M., Switzer, P. and Craig, M.D., 1988, A transformation for ordering multispectral data in terms of image quality with implications for noise removal: IEEE Trans. Geosci. Remote Sensing, 26, 65–74.
Hovgaard, J. and Grasty, R.L., 1997, Reducing statistical noise in airborne gamma-ray data through spectral component analysis: in Gubins, A.G., ed., Proceed. Exploration 97: Fourth Decennial Internat. Conf. Mineral Exploration, 753–764.
IAEA, 1991, Airborne gamma-ray spectrometer surveying: Internat. Atomic Energy Agency, Technical Report Series, No 323.
Mathis, G.L., 1987, Smoothing spectral gamma logs: a simple but effective technique: Geophysics, 52, 363–367.
Minty, B.R.S., 1992, Airborne gamma-ray spectrometr]ic background estimation using full spectrum analysis: Geophysics, 57, 279–287.
Minty, B.R.S., Luyendyk, A.P.J. and Brodie, R.C., 1997, Calibration and data processing for airborne gamma-ray spectrometry: AGSO J. Aust. Geol. Geophys., 17,51–62.
Nielson, A.A., 1994, Analysis of regularly and irregularly sampled spatial, multivariate, and multi-temporal data: PhD thesis, Tech. Univ. of Denmark.
Olsen, Si, 1993, Estimation of noise in images: An evaluation: Graphical Models and Image Processing, 55, 319–323.
Tammenmaa, J., Grasty, R.L. and Peltoniemi, M., 1976, The reduction of statistical noise in airborne radiometric data: Can. J. Earth Sci., 13,1351–1357.

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Article Type: Research Article

Keyword(s): Gamma-ray Aerial Noise Reduction Statistics

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Noise reduction of aerial gamma-ray surveys

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