Discriminating image textures with the multiscale two-dimensional complexity-entropy causality plane
- Autores
- Zunino, Luciano José; Ribeiro, Haroldo V.
- Año de publicación
- 2016
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- 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.
Facultad de Ingeniería
Centro de Investigaciones Ópticas - Materia
-
Ingeniería
Texture images
Roughness
Entropy
Complexity
Ordinal patterns probabilities
Multiscale analysis - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/4.0/
- Repositorio
.jpg)
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/130624
Ver los metadatos del registro completo
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Discriminating image textures with the multiscale two-dimensional complexity-entropy causality planeZunino, Luciano JoséRibeiro, Haroldo V.IngenieríaTexture imagesRoughnessEntropyComplexityOrdinal patterns probabilitiesMultiscale analysisThe 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.Facultad de IngenieríaCentro de Investigaciones Ópticas2016-10info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArticulohttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdf679-688http://sedici.unlp.edu.ar/handle/10915/130624enginfo:eu-repo/semantics/altIdentifier/issn/0960-0779info:eu-repo/semantics/altIdentifier/arxiv/1609.01625info:eu-repo/semantics/altIdentifier/doi/10.1016/j.chaos.2016.09.005info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/4.0/Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-17T10:13:58Zoai:sedici.unlp.edu.ar:10915/130624Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-17 10:13:58.287SEDICI (UNLP) - Universidad Nacional de La Platafalse |
| dc.title.none.fl_str_mv |
Discriminating image textures with the multiscale two-dimensional complexity-entropy causality plane |
| title |
Discriminating image textures with the multiscale two-dimensional complexity-entropy causality plane |
| spellingShingle |
Discriminating image textures with the multiscale two-dimensional complexity-entropy causality plane Zunino, Luciano José Ingeniería Texture images Roughness Entropy Complexity Ordinal patterns probabilities Multiscale analysis |
| title_short |
Discriminating image textures with the multiscale two-dimensional complexity-entropy causality plane |
| title_full |
Discriminating image textures with the multiscale two-dimensional complexity-entropy causality plane |
| title_fullStr |
Discriminating image textures with the multiscale two-dimensional complexity-entropy causality plane |
| title_full_unstemmed |
Discriminating image textures with the multiscale two-dimensional complexity-entropy causality plane |
| title_sort |
Discriminating image textures with the multiscale two-dimensional complexity-entropy causality plane |
| dc.creator.none.fl_str_mv |
Zunino, Luciano José Ribeiro, Haroldo V. |
| author |
Zunino, Luciano José |
| author_facet |
Zunino, Luciano José Ribeiro, Haroldo V. |
| author_role |
author |
| author2 |
Ribeiro, Haroldo V. |
| author2_role |
author |
| dc.subject.none.fl_str_mv |
Ingeniería Texture images Roughness Entropy Complexity Ordinal patterns probabilities Multiscale analysis |
| topic |
Ingeniería Texture images Roughness Entropy Complexity Ordinal patterns probabilities Multiscale analysis |
| dc.description.none.fl_txt_mv |
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. Facultad de Ingeniería Centro de Investigaciones Ópticas |
| description |
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. |
| publishDate |
2016 |
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2016-10 |
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info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Articulo http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
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article |
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publishedVersion |
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http://sedici.unlp.edu.ar/handle/10915/130624 |
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eng |
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eng |
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