Result: Image Analysis: Focus on Texture Similarity
Title:
Image Analysis: Focus on Texture Similarity
Source:
PERCEPTION-BASED MEDIA PROCESSINGProceedings of the IEEE. 101(9):2044-2057
Publisher Information:
New York, NY: Institute of Electrical and Electronics Engineers, 2013.
Publication Year:
2013
Physical Description:
print, 85 ref
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Logiciel, Software, Organisation des mémoires. Traitement des données, Memory organisation. Data processing, Systèmes d'information. Bases de données, Information systems. Data bases, Intelligence artificielle, Artificial intelligence, Reconnaissance des formes. Traitement numérique des images. Géométrie algorithmique, Pattern recognition. Digital image processing. Computational geometry, Telecommunications et theorie de l'information, Telecommunications and information theory, Théorie de l'information, du signal et des communications, Information, signal and communications theory, Théorie du signal et des communications, Signal and communications theory, Codage, codes, Coding, codes, Analyse contenu, Content analysis, Análisis contenido, Analyse image, Image analysis, Análisis imagen, Analyse texture, Texture analysis, Análisis textura, Compression donnée, Data compression, Compresión dato, Compression image, Image compression, Compresión imagen, Compression sans perte, Lossless compression, Compresión sin pérdida, Modélisation, Modeling, Modelización, Métrique, Metric, Métrico, Perception sensorielle, Sensorial perception, Percepción sensorial, Texture, Textura, Traitement image, Image processing, Procesamiento imagen, Validation, Validación, Vision ordinateur, Computer vision, Visión ordenador, Codage image, Image coding, Codificación de imágenes, Recherche par contenu, Content-based retrieval, Búsqueda por Contenidos, Segmentation image, Image segmentation, Segmentación de imágenes, Similitude structurale, Structural similarity, Similitud estructural, Matched-texture coding, structural similarity metrics, structurally lossless compression
Document Type:
Academic journal
Article
File Description:
text
Language:
English
Author Affiliations:
Department of Electrical Engineering and Computer Science, Northwestern University, Evanston, IL 60208, United States
Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, United States
Faculty of Industrial Design Engineering, Delft University of Technology, Delft 2628 CE, Netherlands
FutureWei Technologies, Santa Clara, CA 95050, United States
Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, United States
Faculty of Industrial Design Engineering, Delft University of Technology, Delft 2628 CE, Netherlands
FutureWei Technologies, Santa Clara, CA 95050, United States
ISSN:
0018-9219
Rights:
Copyright 2014 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Telecommunications and information theory
Telecommunications and information theory
Accession Number:
edscal.27735601
Database:
PASCAL Archive
Further Information
Texture is an important visual attribute both for human perception and image analysis systems. We review recently proposed texture similarity metrics and applications that critically depend on such metrics, with emphasis on image and video compression and content-based retrieval. Our focus is on natural textures and structural texture similarity metrics (STSIMs). We examine the relation of STSIMs to existing models of texture perception, texture analysis/synthesis, and texture segmentation. We emphasize the importance of signal characteristics and models of human perception, both for algorithm development and testing/validation.