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Reports (Research Report) Year : 2011

Component-trees and multivalued images: Structural Properties

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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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Dates and versions

inria-00611714 , version 1 (27-07-2011)
inria-00611714 , version 2 (20-10-2011)
inria-00611714 , version 3 (26-02-2018)

Identifiers

  • HAL Id : inria-00611714 , version 2

Cite

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