期刊
CHAOS SOLITONS & FRACTALS
卷 91, 期 -, 页码 679-688出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chaos.2016.09.005
关键词
Texture images; Roughness; Entropy; Complexity; Ordinal patterns probabilities; Multiscale analysis
资金
- Consejo Nacional de Investigaciones Cientificas y Tecnicas (CONICET), Argentina
- Universidad Nacional de La Plata, Argentina [11/I170]
- CNPq [440650/2014-3]
The aim of this paper is to further explore the usefulness of the two-dimensional complexity-entropy causality plane as a texture image descriptor. A multiscale generalization is introduced in order to distinguish between different roughness features of images at small and large spatial scales. Numerically generated two-dimensional structures are initially considered for illustrating basic concepts in a controlled framework. Then, more realistic situations are studied. Obtained results allow us to confirm that intrinsic spatial correlations of images are successfully unveiled by implementing this multiscale symbolic information-theory approach. Consequently, we conclude that the proposed representation space is a versatile and practical tool for identifying, characterizing and discriminating image textures. (C) 2016 Elsevier Ltd. All rights reserved.
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