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Self-dual Attribute Profiles for the Analysis of Remote Sensing Images

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 6671))

Abstract

The spatial relations are essential information that should be considered when analyzing remote sensing images. Attribute profiles (combinations of an anti-granulometry and a granulometry computed with connected operators based on attributes) can be employed for the modeling of the spatial information of the surveyed scene. In this paper we propose self-dual attribute profiles which are attribute profiles computed on an inclusion tree with self-dual operators. The proposed variant of the attribute profile was effectively considered for the classification of a very high geometrical resolution remote sensing image.

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Dalla Mura, M., Benediktsson, J.A., Bruzzone, L. (2011). Self-dual Attribute Profiles for the Analysis of Remote Sensing Images. In: Soille, P., Pesaresi, M., Ouzounis, G.K. (eds) Mathematical Morphology and Its Applications to Image and Signal Processing. ISMM 2011. Lecture Notes in Computer Science, vol 6671. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21569-8_28

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  • DOI: https://doi.org/10.1007/978-3-642-21569-8_28

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-21568-1

  • Online ISBN: 978-3-642-21569-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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