Refining region estimates for post-processing image classification

Paul L. Rosin

doi:10.1117/12.196718

30 December 1994 Refining region estimates for post-processing image classification

Paul L. Rosin

Proceedings Volume 2315, Image and Signal Processing for Remote Sensing; (1994) https://doi.org/10.1117/12.196718
Event: Satellite Remote Sensing, 1994, Rome, Italy

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

Citation Download Citation

Paul L. Rosin "Refining region estimates for post-processing image classification", Proc. SPIE 2315, Image and Signal Processing for Remote Sensing, (30 December 1994); https://doi.org/10.1117/12.196718

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