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Proceedings Paper

Refining region estimates for post-processing image classification
Author(s): Paul L. Rosin
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Paper Abstract

This paper describes a method for post-processing classified images to enable generalisation to be performed whilst maintaining or improving the accuracy of region boundaries. This is achieved by performing region growing, and incorporates both spatial context and spectral information. In contrast, few classifiers use any spatial context, and many post-processing techniques, such as iterative majority filtering, discard all spectral information. If class models are available these can also be included in the region growing process, otherwise, the algorithm operates in a data-driven mode, and locally estimates models for each region.1

Paper Details

Date Published: 30 December 1994
PDF: 11 pages
Proc. SPIE 2315, Image and Signal Processing for Remote Sensing, (30 December 1994); doi: 10.1117/12.196718
Show Author Affiliations
Paul L. Rosin, Institute for Remote Sensing Applications (United Kingdom)


Published in SPIE Proceedings Vol. 2315:
Image and Signal Processing for Remote Sensing
Jacky Desachy, Editor(s)

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