Colour Image Filtering with Component-Graphs

Mathematical morphology, initially devoted to binary and grey-level image processing, also offers opportunities to develop efficient tools for multivalued - and in particular, colour - images. In this context, connected operators are increasingly considered as a relevant way to obtain such tools, mainly for image filtering and segmentation purposes. In this article, we focus on connected operators based on component-trees and their extension to multivalued images, namely component-graphs. Beyond the classical colour-handling strategies, we show how component-graphs can be algorithmically used to efficiently handle the whole structural information gathered by colour spaces, in order to finally design original image filtering tools.

[1]  Philippe Salembier,et al.  Antiextensive connected operators for image and sequence processing , 1998, IEEE Trans. Image Process..

[2]  Sébastien Lefèvre,et al.  A comparative study on multivariate mathematical morphology , 2007, Pattern Recognit..

[3]  Philippe Salembier,et al.  Binary partition tree as an efficient representation for image processing, segmentation, and information retrieval , 2000, IEEE Trans. Image Process..

[4]  Ronald Jones,et al.  Connected Filtering and Segmentation Using Component Trees , 1999, Comput. Vis. Image Underst..

[5]  Hugues Talbot,et al.  Mathematical Morphology: from theory to applications , 2013 .

[6]  Alfred V. Aho,et al.  The Transitive Reduction of a Directed Graph , 1972, SIAM J. Comput..

[7]  Ronald Jones,et al.  Attribute Openings, Thinnings, and Granulometries , 1996, Comput. Vis. Image Underst..

[8]  Thierry Géraud,et al.  A Comparison of Many Max-tree Computation Algorithms , 2013, ISMM.

[9]  Pascal Monasse,et al.  Scale-Space from a Level Lines Tree , 2000, J. Vis. Commun. Image Represent..

[10]  Jean Paul Frédéric Serra.  Tutorial on Connective Morphology , 2012, IEEE Journal of Selected Topics in Signal Processing.

[11]  M.H.F. Wilkinson,et al.  Connected operators , 2009, IEEE Signal Processing Magazine.

[12]  Henk J. A. M. Heijmans,et al.  Theoretical Aspects of Gray-Level Morphology , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[13]  J. W. Modestino,et al.  Flat Zones Filtering, Connected Operators, and Filters by Reconstruction , 1995 .

[14]  Laurent Najman,et al.  Discrete Set-Valued Continuity and Interpolation , 2013, ISMM.

[15]  Nicolas Passat,et al.  Towards Connected Filtering Based on Component-Graphs , 2013, ISMM.

[16]  Nicolas Passat,et al.  An extension of component-trees to partial orders , 2009, 2009 16th IEEE International Conference on Image Processing (ICIP).

[17]  Nicolas Passat,et al.  Component-Trees and Multivalued Images: Structural Properties , 2013, Journal of Mathematical Imaging and Vision.

[18]  Nicolas Passat,et al.  Multivalued Component-Tree Filtering , 2014, 2014 22nd International Conference on Pattern Recognition.

[19]  Pierre Soille,et al.  Constrained connectivity for hierarchical image partitioning and simplification , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[20]  Nicolas Passat,et al.  Component-Trees and Multi-value Images: A Comparative Study , 2009, ISMM.

[21]  Nicolas Passat,et al.  Component-Hypertrees for Image Segmentation , 2011, ISMM.

[22]  Hervé Le Men,et al.  Scale-Sets Image Analysis , 2005, International Journal of Computer Vision.

[23]  Hugues Talbot,et al.  Semi-connections and Hierarchies , 2013, ISMM.

[24]  Hui Gao,et al.  Concurrent Computation of Attribute Filters on Shared Memory Parallel Machines , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.