Distributed Component Forests in 2-D: Hierarchical Image Representations Suitable for Tera-Scale Images

Simon Gazagnes*, Michael H. F. Wilkinson

*Bijbehorende auteur voor dit werk

OnderzoeksoutputAcademicpeer review

4 Citaten (Scopus)
16 Downloads (Pure)


The standard representations known as component trees, used in morphological connected attribute filtering and multi-scale analysis, are unsuitable for cases in which either the image itself or the tree do not fit in the memory of a single compute node. Recently, a new structure has been developed which consists of a collection of modified component trees, one for each image tile. It has to-date only been applied to fairly simple image filtering based on area. In this paper, we explore other applications of these distributed component forests, in particular to multi-scale analysis such as pattern spectra, and morphological attribute profiles and multi-scale leveling segmentations.

Originele taal-2English
Aantal pagina's22
TijdschriftInternational Journal of Pattern Recognition and Artificial Intelligence
Nummer van het tijdschrift11 SI
Vroegere onlinedatum7-mrt-2019
StatusPublished - okt-2019

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