Al Momani, Bilal, Morrow, Philip and McClean, Sally (2007) Knowledge-based semi-supervised satellite image classification. In: 9th International Symposium on Signal Processing and Its Applications, 2007 (ISSPA 2007). IEEE Computer Society. 4 pp. [Conference contribution]
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Spectral information on its own has proven to be insufficient for classification of remotely sensed images. In general, it is difficult to distinguish between types of land-cover classes that have similar or identical spectral signatures from remotely sensed data. Contextual data can be dasiafusedpsila with spectral data to improve the accuracy of classification algorithms. In this paper we use Dempster-Shafer theory of evidence to fuse the output of a semi-supervised classification (SSC) technique with contextual data in the form of a digital elevation model. The final classification accuracy is shown to improve when using this approach.
|Item Type:||Conference contribution (Paper)|
|Faculties and Schools:||Faculty of Computing & Engineering|
Faculty of Computing & Engineering > School of Computing and Information Engineering
|Research Institutes and Groups:||Computer Science Research Institute|
Computer Science Research Institute > Information and Communication Engineering
|Deposited By:||Professor Philip Morrow|
|Deposited On:||04 May 2010 08:41|
|Last Modified:||09 May 2016 11:01|
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