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Descripción
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| The object-based image analysis is one of the most commonly used strategies for processing high spatial resolution images. A prerequisite to object-based image analysis is image segmentation, which is normally defined as the subdivision of an image into separated regions. In this study, we present the evaluation of a new unsupervised image segmentation methodology based on a self-calibrating region growing approach. This is implemented in ISEG (Image Segmentation), our image segmentation software with its self-calibration framework for getting initial parameters. In the evaluation, the obtained good results show the optimization of the segmentation quality jointly with the computational efficiency. | |
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Internacional
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No |
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DOI
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Edición del Libro
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Editorial del Libro
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Carmen Recondo Gonzalez y Enrique Pendas Molina ed. |
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ISBN
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00-0000-000-0 |
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Serie
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Título del Libro
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Bosques y Cambio Climático |
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Desde página
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529 |
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Hasta página
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532 |