Abstract
Most of the current satellite image classification methods consider rough boundaries among homogeneous regions. However; real images contain transition regions where pixels belong, at different degrees, to different classes. With this motivation, in this paper we propose a satellite image classification method that allows the identification of transition regions among homogeneous regions. Our solution is based on Soft Computing because of its ability to handle the uncertainties present in nature. We present our method as well as preliminary results that show how our method is able to solve real world problems.
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Morales, J., Gonzalez, J.A., Reyes-Garcia, C.A., Altamirano, L. (2010). A Soft Computing Approach for Obtaining Transition Regions in Satellite Images . In: Huang, DS., Zhao, Z., Bevilacqua, V., Figueroa, J.C. (eds) Advanced Intelligent Computing Theories and Applications. ICIC 2010. Lecture Notes in Computer Science, vol 6215. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14922-1_20
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DOI: https://doi.org/10.1007/978-3-642-14922-1_20
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14921-4
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