A novel approach to the automatic classiJcation of remote 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 togethex 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.
Remote Sensed Images Segmentation through Shape Refinement
GRASSO, Giorgio Mario;
2001-01-01
Abstract
A novel approach to the automatic classiJcation of remote 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 togethex 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.Pubblicazioni consigliate
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