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30 December 1994 Refining region estimates for post-processing image classification
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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.1
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Paul L. Rosin "Refining region estimates for post-processing image classification", Proc. SPIE 2315, Image and Signal Processing for Remote Sensing, (30 December 1994);

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