An entropy-based approach to automatic image segmentation of satellite images |
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Authors: | Andre L. Barbieri G.F. de Arruda Francisco A. Rodrigues Odemir M. Bruno Luciano da Fontoura Costa |
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Affiliation: | a Instituto de Física de São Carlos, Universidade de São Paulo, São Carlos, SP, PO Box 369, 13560-970, Brazilb Institute of Science and Technology for Complex Systems, Brazilc Departamento de Matemática Aplicada e Estatística, Instituto de Ciências Matemáticas e de Computação, Universidade de São Paulo, São Carlos, SP, PO Box 668, 13560-970, Brazil |
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Abstract: | An entropy-based image segmentation approach is introduced and applied to color images obtained from Google Earth. Segmentation refers to the process of partitioning a digital image in order to locate different objects and regions of interest. The application to satellite images paves the way to automated monitoring of ecological catastrophes, urban growth, agricultural activity, maritime pollution, climate changing and general surveillance. Regions representing aquatic, rural and urban areas are identified and the accuracy of the proposed segmentation methodology is evaluated. The comparison with gray level images revealed that the color information is fundamental to obtain an accurate segmentation. |
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Keywords: | Entropy Information theory Pattern recognition Image analysis |
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