Abstract
The multispectral or vector character of most remote sensing image data renders it amenable to spectral transformations that generate new sets of image components or bands. These components then represent an alternative description of the data, in which the new components of a pixel vector are related to its old brightness values in the original set of spectral bands via a linear operation. The transformed image may make evident features not discernable in the original data or alternatively it might be possible to preserve the essential information content of the image (for a given application) with a reduced number of the transformed dimensions. The last point has significance for displaying data in the three dimensions available on a colour monitor or in colour hardcopy, and for transmission and storage of data.
This is a preview of subscription content, log in via an institution to check access.
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 for Chapter 6
N. Ahmed and K.R. Rao, 1975: Orthogonal Transforms for Digital Signal Processing, Berlin, Springer-Verlag.
H.C. Andrews, 1972: Introduction to Mathematical Techniques in Pattern Recognition, New York, Wiley.
E.F. Byrne, P.F. Crapper and K.K. Mayo, 1980: Monitoring Land-Cover Change by Principal Components Analysis of Multitemporal Landsat Data. Remote Sensing of Environment, 10, 175–184.
N.A. Campbell, 1996: The Decorrelation Stretch Transformation. Int. J. Remote Sensing, 17, 1939–1949.
E. P. Crist and R. T. Kauth, 1986: The Tasseled Cap De-Mystified. Photogrammetric Engineering and Remote Sensing, 52, 81–86.
R.C. Gonzalez and R.E. Woods, 1992: Digital Image Processing, Mass., Addison-Wesley.
P.J. Howarth and E. Boasson, 1983: Landsat Digital Enhancements for Change Detection in Urban Environments. Remote Sensing of Environment, 13, 149–160.
S.E. Ingebritsen and R.JP. Lyon, 1985: Principal Components Analysis of Multitemporal Image Pairs. Int. I Remote Sensing, 6, 687–696.
S.K. Jensen and F.A. Waltz, 1979: Principal Components Analysis and Canonical Analysis in Remote Sensing. Proc. American Photogrammetric Soc. 45th Ann. Meeting, 337-348.
R. J. Kauth and G.S. Thomas, 1976: The Tasseled Cap — A Graphic Description of the Spectral-Temporal Development of Agricultural Crops as Seen by Landsat. Proc. LARS 1976 Symp. on Machine Process. Remotely Sensed Data, Purdue University.
J. A. Richards, 1984: Thematic Mapping from Multitemporal Image Data Using the Principal Components Transformation. Remote Sensing of Environment, 16, 35–46.
A. Santisteban and L. Muñoz, 1978: Principal Components of a Multispectral Image: Application to a Geologic Problem. IBM J. Research and Development, 22, 444–454.
J.M. Soha and A.A. Schwartz, 1978: Multispectral Histogram Normalization Contrast Enhancement. Proc. 5th Canadian Symp. on Remote Sensing, 86-93.
P.H. Swain and S.M. Davis (Eds), 1978: Remote Sensing: The Quantitative Approach, New York, McGraw-Hill.
M. M. Taylor, 1973: Principal Components Colour Display of ERTS Imagery. Third Earth Resources Technology Satellite-1 Symposium, NASA SP-351, 1877-1897.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 1999 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Richards, J.A., Jia, X. (1999). Multispectral Transformations of Image Data. In: Remote Sensing Digital Image Analysis. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-03978-6_6
Download citation
DOI: https://doi.org/10.1007/978-3-662-03978-6_6
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-03980-9
Online ISBN: 978-3-662-03978-6
eBook Packages: Springer Book Archive