Overview

This is a reference for both academic and professional researchers in the fields of image technology, image processing and coding, image display, and image quality. It bridges the gap between academic research on visual perception and image quality and applications of such research in the design of imaging systems. This book has been written from the point of view of an electrical engineer interested in the display, processing and coding of images, and frequently involved in applying knowledge from visual psychophysics, experimental psychology, statistics, and so on, to the design of imaging systems. It focuses on the exchange of ideas between technical disciplines in image technology design (such as image display or printer design and image processing) and visual psychophysics. This is accomplished by the consistent use of a single mathematical approach (based on linear vector spaces) throughout. Known facts from colour vision, image sampling and quantization are given a new formulation and, in some instances, a new interpretation. The book should also be of interest to those working in signal processing, linear algebra, visual (colour/spatial) perception, psychophysics, psychometrics and statistics.

Full Product Details

Author:   Jean-Bernard Martens
Publisher:   Springer-Verlag New York Inc.
Imprint:   Springer-Verlag New York Inc.
Edition:   2003 ed.
Volume:   735
Dimensions:   Width: 15.50cm , Height: 3.10cm , Length: 23.50cm
Weight:   2.150kg
ISBN:  

9781402074615

ISBN 10:   1402074611
Pages:   544
Publication Date:   31 May 2003
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

1. Visual Perception and Linear System Theory.- 1 Introduction.- 2 Linear Systems.- 3 Electromagnetic Radiation and Radiometry.- 4 Color Perception.- 5 Brightness Matching.- 6 Color Matching.- 2. Linear System Theory and Vector Spaces.- 1 Introduction.- 2 Signals and Vectors.- 3 Vector Norms and Banach Spaces.- 4 Linear Operators between Banach Spaces.- 5 Vector Lengths and Hilbert Spaces.- 6 Linear Operators between Hilbert Spaces.- 3. Color Perception and Colorimetry.- 1 Introduction.- 2 Fundamental Color Space.- 3 Color Diagram.- 4 Photometry.- 5 Colorimetry.- 4. Color Management.- 1 Introduction.- 2 Additive Color Displays.- 3 Multiplicative Color Displays.- 4 Standardized Color Coordinates.- 5 Image Sensors.- 6 Reproducing Reproductions.- 7 Color Reproduction and Image Quality.- 5. Psychophysical Measurement and Modelling of Image Quality.- 1 Introduction.- 2 Example of Multidimensional Modelling.- 3 Psychophysical Measurement.- 4 Psychophysical Procedures.- 5 Multidimensional Modelling of Image Quality.- 6 MDS Modelling of Continuous Data.- 7 Examples of Continuous Data Analysis.- 8 MDS Modelling of Discrete Data.- 9 Examples of Discrete Data Analysis.- 10 Summary.- 6. Discrete Periodic Signals and Fourier Transformations.- 1 Introduction.- 2 One-dimensional Signal Transformations.- 3 Lattices.- 4 Multi-dimensional Signal Transformations.- 7. Image Sampling and Interpolation.- 1 Introduction.- 2 Sampling of Periodic Signals.- 3 Comparing Original and Interpolated Signals.- 4 Inverse Operators.- 5 Perceptual Assessment.- 8. Spatio-Temporal Characteristics of The Human Visual System.- 1 Introduction.- 2 Eye - Optical Transfer Function (OTF).- 3 Contrast Sensitivity Function (CSF).- 4 CIELAB Extensions.- 9. Optimizing Sampling Structures.- 1 Introduction.- 2 SamplingLattice Optimization.- 3 Display Function Optimization.- 4 Sampling Function Optimization.- 10. Image Quantization.- 1 Introduction.- 2 Quantization with Bounded Distortion.- 3 Statistical Quantization.- 4 Uniform Quantization.- 5 Dithering.- 6 Ordered Dithering.- 7 Noise Dithering.- 8 Error Diffusion.- 9 Experimental Comparison.- 10 Quantization of Color Images.- 11. Double-Ended Instrumental Models of Image Quality.- 1 Introduction.- 2 Instrumental Dissimilarity Measures.- 3 Performance of Double-Ended Measures.- 4 Conclusions.- 12. Single-Ended Instrumental Models of Image Quality.- 1 Introduction.- 2 Computational Approach.- 3 Feature Detection.- 4 Edge Parameter Estimation.- 5 Images with Correlated Noise.- 6 Images with Noise and Blur.- 7 JPEG-Coded Images.- 8 Conclusions.- References.

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