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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.

Additional information

Authors: ROSIN P L, JRC Ispra (IT)
Bibliographic Reference: Paper presented: The European Symposium on Satellite Remote Sensing, Roma (IT), September 26-30, 1994
Availability: Available from (1) as Paper EN 38600 ORA
Record Number: 199411299 / Last updated on: 1994-12-06
Original language: en
Available languages: en