Next Article in Journal
Denoising of X-ray Images Using the Adaptive Algorithm Based on the LPA-RICI Algorithm
Next Article in Special Issue
An Overview of Deep Learning Based Methods for Unsupervised and Semi-Supervised Anomaly Detection in Videos
Previous Article in Journal
Open Datasets and Tools for Arabic Text Detection and Recognition in News Video Frames
Previous Article in Special Issue
Baseline Fusion for Image and Pattern Recognition—What Not to Do (and How to Do Better)
Article Menu
Issue 2 (February) cover image

Export Article

Open AccessArticle
J. Imaging 2018, 4(2), 33;

Partition and Inclusion Hierarchies of Images: A Comprehensive Survey

1,†,* , 2,†
Lincoln Centre for Autonomous Systems Research, University of Lincoln, Lincoln LN6 7TS, UK
Univ. Rennes I, UMR 6074 IRISA, Campus de Beaulieu, 35042 Rennes, France
Univ. Bretagne Sud, UMR 6074, IRISA, F-56000 Vannes, France
These authors contributed equally to this work.
Author to whom correspondence should be addressed.
Received: 3 December 2017 / Revised: 22 January 2018 / Accepted: 25 January 2018 / Published: 1 February 2018
(This article belongs to the Special Issue Computer Vision and Pattern Recognition)
Full-Text   |   PDF [810 KB, uploaded 8 February 2018]   |  


The theory of hierarchical image representations has been well-established in Mathematical Morphology, and provides a suitable framework to handle images through objects or regions taking into account their scale. Such approaches have increased in popularity and been favourably compared to treating individual image elements in various domains and applications. This survey paper presents the development of hierarchical image representations over the last 20 years using the framework of component trees. We introduce two classes of component trees, partitioning and inclusion trees, and describe their general characteristics and differences. Examples of hierarchies for each of the classes are compared, with the resulting study aiming to serve as a guideline when choosing a hierarchical image representation for any application and image domain. View Full-Text
Keywords: component trees; hierarchical image representation; Mathematical Morphology; hierarchy indexing component trees; hierarchical image representation; Mathematical Morphology; hierarchy indexing

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Bosilj, P.; Kijak, E.; Lefèvre, S. Partition and Inclusion Hierarchies of Images: A Comprehensive Survey. J. Imaging 2018, 4, 33.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
J. Imaging EISSN 2313-433X Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top