Methods for Contextual Classification of Remotely Sensed Data

The Southern African Institute of Mining and Metallurgy
L. P. Fatti
Organization:
The Southern African Institute of Mining and Metallurgy
Pages:
17
File Size:
946 KB
Publication Date:
Jan 1, 1987

Abstract

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An important feature affecting the classification of a remotely sensed scene is that the data are, in general, spatially correlated. Various approaches are discussed towards incorporating the correlation between neighbouring pixels when they are classified on the basis of their spectral reflectance data.
Citation

APA: L. P. Fatti  (1987)  Methods for Contextual Classification of Remotely Sensed Data

MLA: L. P. Fatti Methods for Contextual Classification of Remotely Sensed Data. The Southern African Institute of Mining and Metallurgy, 1987.

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