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Remote sensed images segmentation through shape refinement

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4 Author(s)
Gallo, G. ; Dipartimento di Matematica e Inf., Catania Univ., Italy ; Grasso, G. ; Nicotra, S. ; Pulvirenti, A.

A novel approach to the automatic classification of remotely sensed images is proposed. This approach is based on a three-phase procedure: first pixels which belong to the areas of interest with large likelihood are selected as seeds; second the seeds are refined into connected shapes using two well-known image processing techniques; third the results of the shape refinement algorithms are merged together. The initial seed extraction is performed using a simple thresholding strategy applied to NDVI4-3 index. Subsequently shape refinement through seeded region growing and watershed decomposition is applied; finally a merging procedure is applied to build likelihood maps. Experimental results are presented to analyze the correctness and robustness of the method in recognizing vegetation areas around Mount Etna

Published in:

Image Analysis and Processing, 2001. Proceedings. 11th International Conference on

Date of Conference:

26-28 Sep 2001