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Morphological Scale Space and Mathematical Morphology

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1682))

Abstract

It is well known that a conveniently rescaled iterated convo- lution of a linear positive kernel converges to a Gaussian. Therefore, all iterative linear smoothing methods of a signal or an image boils down to the application to the signal of the Heat Equation. In this survey, we explain how a similar analysis can be performed for image iterative smoothing by contrast invariant monotone operators. In particular, we prove that all iterated affine and contrast invariant monotone opera- tors are equivalent to the unique affine invariant curvature motion. We also prove that under very broad conditions, weighted median filters are equivalent to the Mean Curvature Motion Equation.

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© 1999 Springer-Verlag Berlin Heidelberg

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Cao, F. (1999). Morphological Scale Space and Mathematical Morphology. In: Nielsen, M., Johansen, P., Olsen, O.F., Weickert, J. (eds) Scale-Space Theories in Computer Vision. Scale-Space 1999. Lecture Notes in Computer Science, vol 1682. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48236-9_15

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  • DOI: https://doi.org/10.1007/3-540-48236-9_15

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-66498-7

  • Online ISBN: 978-3-540-48236-9

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