Adaptive Satellite Images Segmentation by Level Set Multiregion Competition

In this paper, we present an adaptive variational segmentation algorithm of spectral-texture regions in satellite images using level set. Satellite images contain both textured and non-textured regions, so for each region cues of spectral and texture are integrated according to their discrimination power. Motivated by Fisher-Rao's linear discriminant analysis, two region's weights are defined to code respectively the relevance of spectral and texture cues. Therefore, regions with or without texture are processed in the same framework. The obtained segmentation criterion is minimized via curves evolution within an explicit correspondence between the interiors of evolving curves and regions in segmentation. Thus, an unambiguous segmentation to a given arbitrary number of regions is obtained by the multiregion competition algorithm. Experimental results on both natural and satellite images are shown.

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