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Digital color imaging /

This collective work identifies the latest developments in the field of the automatic processing and analysis of digital color images. For researchers and students, it represents a critical state of the art on the scientific issues raised by the various steps constituting the chain of color image pr...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Fernández-Maloigne, Christine, Robert-Inacio, Frédérique, Macaire, Ludovic
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London : Hoboken : ISTE ; John Wiley & Sons, 2012.
Colección:Digital signal and image processing series.
ISTE.
Temas:
Acceso en línea:Texto completo

MARC

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020 |z 9781848213470 
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082 0 4 |a 535.601/51  |a 535.60151 
049 |a UAMI 
245 0 0 |a Digital color imaging /  |c edited by Christine Fernandez-Maloigne, Frederique Robert-Inacio, [and] Ludovic Macaire. 
260 |a London :  |b ISTE ;  |a Hoboken :  |b John Wiley & Sons,  |c 2012. 
300 |a 1 online resource 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a ISTE 
490 1 |a Digital signal and image processing series 
504 |a Includes bibliographical references and index. 
520 |a This collective work identifies the latest developments in the field of the automatic processing and analysis of digital color images. For researchers and students, it represents a critical state of the art on the scientific issues raised by the various steps constituting the chain of color image processing. It covers a wide range of topics related to computational color imaging, including color filtering and segmentation, color texture characterization, color invariant for object recognition, color and motion analysis, as well as color image and video indexing and retrieval. 
588 0 |a Print version record. 
505 0 |a Cover; Title Page; Copyright Page; Table of Contents; Foreword; Chapter 1. Color Representation and Processing in Polar Color Spaces; 1.1. Introduction; 1.1.1. Notations used in this chapter; 1.2. The HSI triplet; 1.2.1. Intuitive approach: basic concepts and state of the art; 1.2.2. Geometric approach: calculation of polar coordinates; 1.3. Processing of hue: a variable on the unit circle; 1.3.1. Can hue be represented as a scalar?; 1.3.2. Ordering based on distance from a reference hue; 1.3.3. Ordering with multiple references; 1.3.4. Determination of reference hues. 
505 8 |a 1.4. Color morphological filtering in the HSI space1.4.1. Chromatic and achromatic top-hat transforms; 1.4.2. Full ordering using lexicographical cascades; 1.5. Morphological color segmentation in the HSI space; 1.5.1. Color distances and segmentation by connective criteria; 1.5.2. Color gradients and watershed segmentation; 1.6. Conclusion; 1.7. Bibliography; Chapter 2. Adaptive Median Color Filtering; 2.1. Introduction; 2.2. Noise; 2.2.1. Sources of noise; 2.2.2. Noise modeling; 2.3. Nonlinear filtering; 2.3.1. Vector methods; 2.3.2. Median filter using bit mixing. 
505 8 |a 2.4. Median filter: methods derived from vector methods2.4.1. Vector filtering; 2.4.2. Switching vector and peer group filters; 2.4.3. Hybrid switching vector filter; 2.4.4. Fuzzy filters; 2.5. Adaptive filters; 2.5.1. Spatially adaptive filter: generic method; 2.5.2. Spatially adaptive median filter; 2.6. Performance comparison; 2.6.1. FSVF; 2.6.2. FRF; 2.6.3. PGF and FMPGF; 2.6.4. IPGSVF; 2.6.5. Vector filters and spatially adaptive median filter; 2.7. Conclusion; 2.8. Bibliography; Chapter 3. Anisotropic Diffusion PDEs for Regularization of Multichannel Images: Formalisms and Applications. 
505 8 |a 3.1. Introduction3.2. Preliminary concepts; 3.3. Local geometry in multi-channel images; 3.3.1. Which geometric characteristics?; 3.3.2. Geometry estimated using a scalar characteristic; 3.3.3. Di Zenzo multi-valued geometry; 3.4. PDEs for multi-channel image smoothing: overview; 3.4.1. Variational methods; 3.4.2. Divergence PDEs; 3.4.3. Oriented Laplacian PDEs; 3.4.4. Trace PDEs; 3.5. Regularization and curvature preservation; 3.5.1. Single smoothing direction; 3.5.2. Analogy with line integral convolutions; 3.5.3. Extension to multi-directional smoothing; 3.6. Numerical implementation. 
505 8 |a 3.7. Some applications3.8. Conclusion; 3.9. Bibliography; Chapter 4. Linear Prediction in Spaces with Separate Achromatic and Chromatic Information; 4.1. Introduction; 4.2. Complex vector 2D linear prediction; 4.3. Spectral analysis in the IHLS and L*a*b* color spaces; 4.3.1. Comparison of PSD estimation methods; 4.3.2. Study of inter-channel interference associated with color space changing transformations; 4.4. Application to segmentation of textured color images; 4.4.1. Prediction error distribution; 4.4.2. Label field estimation; 4.4.3. Experiments and results; 4.5. Conclusion. 
590 |a ProQuest Ebook Central  |b Ebook Central Academic Complete 
650 0 |a Color  |x Mathematics  |x Research. 
650 0 |a Image processing  |x Mathematics  |x Research. 
650 0 |a Color vision  |x Research. 
650 6 |a Couleur  |x Mathématiques  |x Recherche. 
650 6 |a Traitement d'images  |x Mathématiques  |x Recherche. 
650 6 |a Vision des couleurs  |x Recherche. 
650 7 |a SCIENCE  |x Physics  |x Optics & Light.  |2 bisacsh 
650 7 |a Color vision  |x Research  |2 fast 
700 1 |a Fernández-Maloigne, Christine. 
700 1 |a Robert-Inacio, Frédérique. 
700 1 |a Macaire, Ludovic. 
758 |i has work:  |a Digital color imaging (Text)  |1 https://id.oclc.org/worldcat/entity/E39PCFKd7F3CCq7CYDvrHhd6Vd  |4 https://id.oclc.org/worldcat/ontology/hasWork 
776 0 8 |i Print version:  |a Fernandez-Maloigne, Christine.  |t Digital Color Imaging.  |d Hoboken : Wiley, ©2013  |z 9781848213470 
830 0 |a Digital signal and image processing series. 
830 0 |a ISTE. 
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