title: Directed Connected Operators: Asymmetric Hierarchies for Image Filtering and Segmentation.
abstract: Connected operators provide well-established solutions for digital image processing, typically in conjunction with hierarchical schemes. In graph-based frameworks, such operators basically rely on symmetric adjacency relations between pixels. In this article, we introduce a notion of directed connected operators for hierarchical image processing, by also considering non-symmetric adjacency relations. The induced image representation models are no longer partition hierarchies (i.e., trees), but directed acyclic graphs that generalize standard morphological tree structures such as component trees, binary partition trees or hierarchical watersheds. We describe how to efficiently build and handle these richer data structures, and we illustrate the versatility of the proposed framework in image filtering and image segmentation.
authors.forename: Benjamin
authors.initials: B
authors.lastname: Perret
authors.forename: Jean
authors.initials: J
authors.lastname: Cousty
authors.forename: Olena
authors.initials: O
authors.lastname: Tankyevych
authors.forename: Hugues
authors.initials: H
authors.lastname: Talbot
authors.forename: Nicolas
authors.initials: N
authors.lastname: Passat
mesh_terms: D000465:Algorithms; D016208:Databases, Factual; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D016501:Neurites / Q000648:ultrastructure; D010363:Pattern Recognition, Automated / Q000379:methods*; D012160:Retina / Q000033:anatomy & histology