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Digital color : acquisition, perception, coding and rendering / / edited by Christine Fernández-Maloine, Frédérique Robert-Inacio, Ludovic Macaire
| Digital color : acquisition, perception, coding and rendering / / edited by Christine Fernández-Maloine, Frédérique Robert-Inacio, Ludovic Macaire |
| Pubbl/distr/stampa | London : , : ISTE |
| Descrizione fisica | 1 online resource (330 p.) |
| Disciplina | 006.6 |
| Collana | ISTE |
| Soggetto topico |
Image converters
Digital images Color vision Color photography - Digital techniques |
| ISBN |
1-118-56268-2
1-118-56324-7 1-118-56269-0 1-299-18892-3 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Title Page; Copyright Page; Table of Contents; Foreword; Chapter 1. Colorimetry and Physiology - The LMS Specification; 1.1. Physiological basis; 1.1.1. The photoreceptors; 1.1.2. Retinal organization; 1.1.3. Physiological modeling of visual attributes related to color; 1.2. The XYZ colorimetry: the benchmark model of CIE; 1.3. LMS colorimetry; 1.3.1. LMS fundamentals; 1.3.2. Application of LMS colorimetry; 1.3.3. Color discrimination; 1.4. Colors in their context; 1.4.1. CIECAM02; 1.4.2. Chromatic adaptation; 1.4.3. Partitioning of the perceptual space by the elementary hues
1.5. Conclusion1.6. Bibliography; Chapter 2. Color Constancy; 2.1. Introduction; 2.2. Theoretical preliminaries and problems; 2.2.1. Concept of illuminant; 2.2.2. Concept of objects' reflectance; 2.2.3. Problem of color constancy; 2.3. Color constancy models; 2.3.1. Model of the human visual system; 2.3.2. Von Kries diagonal model; 2.3.3. Land theory; 2.4. Color correction algorithms; 2.4.1. Gray world; 2.4.2. Retinex theory; 2.4.3. Gamut conversion; 2.4.4. Probabilistic methods; 2.4.5. Method based on neural networks; 2.4.6. ACE: automatic color equalization 2.4.7. Methods combining several approaches2.5. Comparison of color constancy algorithms; 2.5.1. Algorithms evaluation; 2.5.2. Examples of applications with specific patterns; 2.6. Conclusion; 2.7. Bibliography; Chapter 3. Color Appearance Models; 3.1. Introduction; 3.2. The two perceptual phenomena of color appearance; 3.3. The main components of a CAM; 3.3.1. Chromatic adaptation models; 3.3.2. The perceptual attributes; 3.3.3. General architecture of CAMs standardized by the CIE; 3.4. The CIECAM02; 3.4.1. Input data; 3.4.2. The chromatic adaptation transform 3.4.3. The appearance attributes3.5. Conclusion; 3.6. Bibliography; Chapter 4. Rendering and Computer Graphics; 4.1. Introduction; 4.2. Reflection and representation models of light sources; 4.2.1. Concept of luminance; 4.2.2. Representation of the light sources; 4.2.3. Reflection and refraction models; 4.3. Simulation of light propagation; 4.3.1. Light propagation model: the rendering equation; 4.3.2. Solution of the rendering equation; 4.4. Display of results; 4.4.1. LDR and HDR Images; 4.4.2. Tone mapping; 4.4.3. Management of spectral aspects; 4.4.4. Computer graphics and perception 4.5. Conclusion4.6. Bibliography; Chapter 5. Image Sensor Technology; 5.1. Photodetection principle; 5.1.1. The photodiode; 5.1.2. The photoMOS; 5.2. Imagers; 5.2.1. CMOS and CCD technologies; 5.2.2. CCD (charge coupled device) imager principle; 5.2.3. CMOS imagers principle; 5.2.4. Photodiode pixel in current mode; 5.2.5. Photodiode pixel in integration mode; 5.3. Spectral sensitivity of imagers; 5.4. Color acquisition systems; 5.5. Through monochrome camera; 5.6. Tri-sensor systems; 5.7. Color camera based on color filter arrays; 5.7.1. Types of filters; 5.8. Variants of integrated sensors 5.8.1. Backside illumination: Sony, Omnivision |
| Record Nr. | UNINA-9910138856003321 |
| London : , : ISTE | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Digital color : acquisition, perception, coding and rendering / / edited by Christine Fernández-Maloine, Frédérique Robert-Inacio, Ludovic Macaire
| Digital color : acquisition, perception, coding and rendering / / edited by Christine Fernández-Maloine, Frédérique Robert-Inacio, Ludovic Macaire |
| Pubbl/distr/stampa | London : , : ISTE |
| Descrizione fisica | 1 online resource (330 p.) |
| Disciplina | 006.6 |
| Collana | ISTE |
| Soggetto topico |
Image converters
Digital images Color vision Color photography - Digital techniques |
| ISBN |
1-118-56268-2
1-118-56324-7 1-118-56269-0 1-299-18892-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Title Page; Copyright Page; Table of Contents; Foreword; Chapter 1. Colorimetry and Physiology - The LMS Specification; 1.1. Physiological basis; 1.1.1. The photoreceptors; 1.1.2. Retinal organization; 1.1.3. Physiological modeling of visual attributes related to color; 1.2. The XYZ colorimetry: the benchmark model of CIE; 1.3. LMS colorimetry; 1.3.1. LMS fundamentals; 1.3.2. Application of LMS colorimetry; 1.3.3. Color discrimination; 1.4. Colors in their context; 1.4.1. CIECAM02; 1.4.2. Chromatic adaptation; 1.4.3. Partitioning of the perceptual space by the elementary hues
1.5. Conclusion1.6. Bibliography; Chapter 2. Color Constancy; 2.1. Introduction; 2.2. Theoretical preliminaries and problems; 2.2.1. Concept of illuminant; 2.2.2. Concept of objects' reflectance; 2.2.3. Problem of color constancy; 2.3. Color constancy models; 2.3.1. Model of the human visual system; 2.3.2. Von Kries diagonal model; 2.3.3. Land theory; 2.4. Color correction algorithms; 2.4.1. Gray world; 2.4.2. Retinex theory; 2.4.3. Gamut conversion; 2.4.4. Probabilistic methods; 2.4.5. Method based on neural networks; 2.4.6. ACE: automatic color equalization 2.4.7. Methods combining several approaches2.5. Comparison of color constancy algorithms; 2.5.1. Algorithms evaluation; 2.5.2. Examples of applications with specific patterns; 2.6. Conclusion; 2.7. Bibliography; Chapter 3. Color Appearance Models; 3.1. Introduction; 3.2. The two perceptual phenomena of color appearance; 3.3. The main components of a CAM; 3.3.1. Chromatic adaptation models; 3.3.2. The perceptual attributes; 3.3.3. General architecture of CAMs standardized by the CIE; 3.4. The CIECAM02; 3.4.1. Input data; 3.4.2. The chromatic adaptation transform 3.4.3. The appearance attributes3.5. Conclusion; 3.6. Bibliography; Chapter 4. Rendering and Computer Graphics; 4.1. Introduction; 4.2. Reflection and representation models of light sources; 4.2.1. Concept of luminance; 4.2.2. Representation of the light sources; 4.2.3. Reflection and refraction models; 4.3. Simulation of light propagation; 4.3.1. Light propagation model: the rendering equation; 4.3.2. Solution of the rendering equation; 4.4. Display of results; 4.4.1. LDR and HDR Images; 4.4.2. Tone mapping; 4.4.3. Management of spectral aspects; 4.4.4. Computer graphics and perception 4.5. Conclusion4.6. Bibliography; Chapter 5. Image Sensor Technology; 5.1. Photodetection principle; 5.1.1. The photodiode; 5.1.2. The photoMOS; 5.2. Imagers; 5.2.1. CMOS and CCD technologies; 5.2.2. CCD (charge coupled device) imager principle; 5.2.3. CMOS imagers principle; 5.2.4. Photodiode pixel in current mode; 5.2.5. Photodiode pixel in integration mode; 5.3. Spectral sensitivity of imagers; 5.4. Color acquisition systems; 5.5. Through monochrome camera; 5.6. Tri-sensor systems; 5.7. Color camera based on color filter arrays; 5.7.1. Types of filters; 5.8. Variants of integrated sensors 5.8.1. Backside illumination: Sony, Omnivision |
| Record Nr. | UNINA-9910822623403321 |
| London : , : ISTE | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Digital color imaging [[electronic resource] /] / edited by Christine Fernandez-Maloigne, Frédérique Robert-Inacio, Ludovic Macaire
| Digital color imaging [[electronic resource] /] / edited by Christine Fernandez-Maloigne, Frédérique Robert-Inacio, Ludovic Macaire |
| Pubbl/distr/stampa | London, : ISTE |
| Descrizione fisica | 1 online resource (368 p.) |
| Disciplina | 535.601/51 |
| Altri autori (Persone) |
Fernandez-MaloigneChristine
Robert-InacioFrédérique MacaireLudovic |
| Collana | Digital signal and image processing series |
| Soggetto topico |
Color - Mathematics - Research
Image processing - Mathematics - Research Color vision - Research |
| ISBN |
1-118-56196-1
1-299-31508-9 1-118-61434-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
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
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 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 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 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 4.6. Bibliography |
| Record Nr. | UNINA-9910139052303321 |
| London, : ISTE | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Digital color imaging [[electronic resource] /] / edited by Christine Fernandez-Maloigne, Frédérique Robert-Inacio, Ludovic Macaire
| Digital color imaging [[electronic resource] /] / edited by Christine Fernandez-Maloigne, Frédérique Robert-Inacio, Ludovic Macaire |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | London, : ISTE |
| Descrizione fisica | 1 online resource (368 p.) |
| Disciplina | 535.601/51 |
| Altri autori (Persone) |
Fernandez-MaloigneChristine
Robert-InacioFrédérique MacaireLudovic |
| Collana | Digital signal and image processing series |
| Soggetto topico |
Color - Mathematics - Research
Image processing - Mathematics - Research Color vision - Research |
| ISBN |
1-118-56196-1
1-299-31508-9 1-118-61434-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
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
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 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 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 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 4.6. Bibliography |
| Record Nr. | UNINA-9910808338703321 |
| London, : ISTE | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||