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

dc.creatorZunino, Luciano José
dc.creatorRibeiro, Haroldo V.
dc.date2016-10
dc.date2022-02-07T16:55:52Z
dc.date.accessioned2023-07-15T04:15:46Z
dc.date.available2023-07-15T04:15:46Z
dc.identifierhttp://sedici.unlp.edu.ar/handle/10915/130624
dc.identifierissn:0960-0779
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/7468876
dc.descriptionThe 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.
dc.descriptionFacultad de Ingeniería
dc.descriptionCentro de Investigaciones Ópticas
dc.formatapplication/pdf
dc.format679-688
dc.languageen
dc.rightshttp://creativecommons.org/licenses/by-nc-sa/4.0/
dc.rightsCreative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
dc.subjectIngeniería
dc.subjectTexture images
dc.subjectRoughness
dc.subjectEntropy
dc.subjectComplexity
dc.subjectOrdinal patterns probabilities
dc.subjectMultiscale analysis
dc.titleDiscriminating image textures with the multiscale two-dimensional complexity-entropy causality plane
dc.typeArticulo
dc.typeArticulo


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