DocumentCode :
788495
Title :
Estimation of Context for Statistical Classification of Multispectral Image Data
Author :
Tilton, James C. ; Vardeman, Stephen B. ; Swain, Philip H.
Author_Institution :
Computer Sciences Corporation, Silver Spring, MD
Issue :
4
fYear :
1982
Firstpage :
445
Lastpage :
452
Abstract :
Recent investigations have demonstrated the effectiveness of a contextual classifier that combines spatial and spectral information employing a general statistical approach [1], [2]. This statistical classification algorithm exploits the tendency of certain ground-cover classes to occur more frequently in some spatial contexts than in others. Indeed, a key input to this algorithm is a statistical characterization of the context: the context function. Here we discuss an unbiased estimator of the context function which, besides having the advantage of statistical unbiasedness, has the additional advantage over other estimation techniques of being amenable to an adaptive implementation in which the context-function estimate varies according to local contextual information. Results from applying the unbiased estimator to the contextual classification of three real Landsat data sets are presented and contrasted with results from noncontextual classifications and from contextual classifications utilizing other context-function estimation techniques.
Keywords :
Application software; Humans; Image analysis; Image texture analysis; Information analysis; Laboratories; Multispectral imaging; Pixel; Remote sensing; Statistics;
fLanguage :
English
Journal_Title :
Geoscience and Remote Sensing, IEEE Transactions on
Publisher :
ieee
ISSN :
0196-2892
Type :
jour
DOI :
10.1109/TGRS.1982.350410
Filename :
4157332
Link To Document :
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