Open AccessHierarchical morphological graph signal multi‐layer decomposition for editing applications
Author(s) -
Lézoray Olivier
Publication year - 2020
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2019.0576
Subject(s) - computer science , polygon mesh , graph , image editing , abstraction , signal processing , tone mapping , mathematical morphology , decomposition , algorithm , theoretical computer science , artificial intelligence , pattern recognition (psychology) , image processing , image (mathematics) , computer vision , computer graphics (images) , telecommunications , dynamic range , philosophy , radar , ecology , epistemology , high dynamic range , biology
The authors address the problem of editing signals such as 2D colour images or 3D coloured meshes that are represented under the general framework of graph signals. As state‐of‐the‐art editing approaches decompose an image into several layers in order to manipulate them, they propose a hierarchical multi‐layer decomposition of graph signals that relies on morphological filtering. Since morphological filtering operators require a complete lattice, a dedicated approach for the morphological processing of vectorial data on graphs is used. By iterating the application of morphological filterings of decreasing sizes, the graph signal is decomposed into several detail layers, each capturing a given detail level. Editing applications such as abstraction, sharpness enhancement and tone mapping are shown to illustrate the benefits of the proposed approach.