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Discriminating image textures with the multiscale two-dimensional complexity-entropy causality plane

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  • Zunino, Luciano
  • Ribeiro, Haroldo V.

Abstract

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.

Suggested Citation

  • Zunino, Luciano & Ribeiro, Haroldo V., 2016. "Discriminating image textures with the multiscale two-dimensional complexity-entropy causality plane," Chaos, Solitons & Fractals, Elsevier, vol. 91(C), pages 679-688.
    • Handle: RePEc:eee:chsofr:v:91:y:2016:i:c:p:679-688
    DOI: 10.1016/j.chaos.2016.09.005
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    References listed on IDEAS

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