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Component-trees and multivalued images: Structural Properties

Abstract : Component-trees model the structure of grey-level images by considering their binary level-sets obtained from successive thresholdings. They also enable to define anti-extensive filtering procedures for such images. In order to extend this image processing approach to any (grey-level or multivalued) images, both the notion of component-tree, and its associated filtering framework, have to be generalised. In this article we first deal with the generalisation of the component-tree structure. We define a new data structure, the component-graph, which extends the notion of component-tree to images taking their values in any (partially or totally) ordered set. The component-graphs are declined in three variants, of increasing richness and size, whose structural properties are studied.
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Contributor : Benoît Naegel Connect in order to contact the contributor
Submitted on : Thursday, October 20, 2011 - 9:43:49 AM
Last modification on : Thursday, October 14, 2021 - 11:06:02 AM
Long-term archiving on: : Saturday, January 21, 2012 - 2:25:23 AM


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  • HAL Id : inria-00611714, version 2


Nicolas Passat, Benoît Naegel. Component-trees and multivalued images: Structural Properties. [Research Report] 2011, pp.10. ⟨inria-00611714v2⟩



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