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Proceedings Paper

Multi-Temporal Classification Of Remote Sensed Data In Image Processors With A Pipeline Architecture
Author(s): J. M. Rebordao; M. C. Proenca
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Paper Abstract

Hierarchical classifiers are discussed and a new implementation in digital image processors with a pipeline architecture is presented. This implementation makes optimal use of the different layers of look up tables that generally exist in all machines with this architecture. Classification can be considered to occur at almost real time, as far as the unit structure of the tree associated to the classifier is concerned. As the hierarchical classifier makes optimal use of all the information available, fast decision rules can be applied in most of the nodes, thus reducing considerably the overall computational burden. An example is provided in the context of classification of multi-temporal remote sensed data. To apply the technique, the evaluation of the features must have been done previously.

Paper Details

Date Published: 5 April 1989
PDF: 18 pages
Proc. SPIE 1075, Digital Image Processing Applications, (5 April 1989); doi: 10.1117/12.952630
Show Author Affiliations
J. M. Rebordao, Laboratorio Nacional de Engenharia e Tecnologia Industrial (LNETI) (Portugal)
M. C. Proenca, Laboratorio Nacional de Engenharia e Tecnologia Industrial (LNETI) (Portugal)

Published in SPIE Proceedings Vol. 1075:
Digital Image Processing Applications
Ying-Wei Lin; Ram Srinivasan, Editor(s)

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