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Descripción
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| With the advent of higher-resolution remote sensing imagery the need for more efficient multi-scale image analysis methods has grown more than ever. This paper presents a superpixelbased methodology for hierarchical image analysis. The use of superpixels as pre-processing block reduces the execution time of the analysis and also provides a good starting point to build meaningful objects at different scales through a merging process. At each scale a set of most representative features are extracted, and then regions of interest are identified through a classification method. Only classes of interest are analyzed in a later segmentation step. | |
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Internacional
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Si |
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DOI
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Edición del Libro
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1 |
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Editorial del Libro
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IOS PRESS |
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ISBN
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978-88-89693-34-6 |
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Serie
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European Association of Remote Sensing Laboratories Symposium Proceedings |
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Título del Libro
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Towards Horizon 2020: Earth Observation and Social Perspectives |
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Desde página
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753 |
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Hasta página
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760 |