Using Dempster-Shafer to Incorporate Knowledge into Satellite Image Classification

B Al_Momani, SI McClean, PJ Morrow

Research output: Contribution to journalArticle

10 Citations (Scopus)

Abstract

Remote sensing imaging techniques make use of data derived from high resolution satellite sensors. Image classification identifies and organises pixels of similar spatial distribution or similar statistical characteristics into the same spectral class (theme). Contextual data can be incorporated, or ‘fused’, with spectral data to improve the accuracy of classification algorithms. In this paper we use Dempster–Shafer’s theory of evidence to achieve this data fusion. Incorporating a Knowledge Base of evidence within the classification process represents a new direction for the development of reliable systems for image classification and the interpretation of remotely sensed data.
LanguageEnglish
Pages161-178
JournalArtificial Intelligence Review
Volume25
Issue number1-2
DOIs
Publication statusPublished - 3 Oct 2007

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image classification
satellite sensor
pixel
satellite image
spatial distribution
remote sensing

Cite this

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Using Dempster-Shafer to Incorporate Knowledge into Satellite Image Classification. / Al_Momani, B; McClean, SI; Morrow, PJ.

In: Artificial Intelligence Review, Vol. 25, No. 1-2, 03.10.2007, p. 161-178.

Research output: Contribution to journalArticle

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