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Morphological Scale-Space Operators for Images Supported on Point Clouds

Abstract : The aim of this paper is to develop the theory, and to propose an algorithm, for morphological processing of images painted on point clouds, viewed as a length metric measure space $(X,d,\mu)$. In order to extend morphological operators to process point cloud supported images, one needs to define dilation and erosion as semigroup operators on $(X,d)$. That corresponds to a supremal convolution (and infimal convolution) using admissible structuring function on $(X,d)$. From a more theoretical perspective, we introduce the notion of abstract structuring functions formulated on length metric Maslov idempotent measurable spaces, which is the appropriate setting for $(X,d)$. In practice, computation of Maslov structuring function is approached by a random walks framework to estimate heat kernel on $(X,d,\mu)$, followed by the logarithmic trick.
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Preprints, Working Papers, ...
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Contributor : Jesus Angulo Connect in order to contact the contributor
Submitted on : Saturday, March 21, 2015 - 4:46:31 PM
Last modification on : Thursday, September 24, 2020 - 4:38:04 PM
Long-term archiving on: : Monday, September 14, 2015 - 6:07:48 AM


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  • HAL Id : hal-01108141, version 2


Jesus Angulo. Morphological Scale-Space Operators for Images Supported on Point Clouds. 2014. ⟨hal-01108141v2⟩



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