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Clustering and Unsupervised Classification

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Remote Sensing Digital Image Analysis

Abstract

The successful application of maximum likelihood classification is dependent upon having delineated correctly the spectral classes in the image data of interest. This is necessary since each class is to be modelled by a normal probability distribution, as discussed in Chap. 8. If a class happens to be multimodal, and this is not resolved, then clearly the modelling cannot be very effective.

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References for Chapter 9

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© 1993 Springer-Verlag Berlin Heidelberg

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Richards, J.A. (1993). Clustering and Unsupervised Classification. In: Remote Sensing Digital Image Analysis. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-88087-2_9

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  • DOI: https://doi.org/10.1007/978-3-642-88087-2_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-58219-9

  • Online ISBN: 978-3-642-88087-2

  • eBook Packages: Springer Book Archive

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