A Transformation for Ordering Multispectral Data in Terms of Image Quality with Implications for Noise Removal

IEEE Transactions on Geoscience and Remote Sensing

Volumn 26, Issue 1, 1988, Pages 65-74

  Green, Andrew A ^a   Berman, Mark ^b   Switzer, Paul ^c   Craig, Maurice D ^a  

^a CSIRO MINERALS   (Australia)

^b CSIRO MATHEMATICAL AND INFORMATION SCIENCES   (Australia)

^c STANFORD UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

IMAGING TECHNIQUES - MATHEMATICAL MODELS;

IMAGE QUALITY; MAXIMUM NOISE FRACTION (MNF) TRANSFORM; MULTISPECTRAL DATA ORDERING; NOISE REMOVAL;

REMOTE SENSING;

EID: 0023854011     PISSN: 01962892     EISSN: 15580644     Source Type: Journal    
DOI: 10.1109/36.3001     Document Type: Article

References (6)

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2. P. J. Ready and P. A. Wintz, “Information extraction, SNR improvement, and data compression in multispectral imagery”, IEEE Trans. Commun., vol. 21, pp. 1123–1130, 1973.
3. A. R. Gillespie, “Digital techniques of image enhancement”, in Remote Sensing in Geology, B. S. Siegal and A. R. Gillespie, Eds. New York: Wiley, 1980, pp. 195–202 and pp. 220–203.
4. J. R. G. Townshend, “Agriculture land-cover discrimination using thematic mapper spectral bands”, Int. J. Remote Sensing, vol. 5, no. 4, pp. 681–698, 1984.
5. P. Switzer and A. Green, “Min/max autocorrelation factors for multivariate spatial imagery”, Dept. of Statistics, Stanford University, Tech. Rep. 6, 1984.
6. M. Berman, “The statistical properties of three noise removal procedures for multichannel remotely sensed data”, CSIRO Division of Mathematics and Statistics Consulting Rep., NSW/85/31/MB9, 1985.