Image Technology Design

by Martens, Jean-Bernard

• ISBN13: 9781402074615
• ISBN10: 1402074611
• Format: Hardcover
• Copyright: 2003-05-01
• Publisher: Kluwer Academic Pub

Summary

Image Technology Design: A Perceptual Approach is an essential 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, etc., 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 color vision, image sampling and quantization are given a new formulation and, in some instances, a new interpretation. Image Technology Design: A Perceptual Approach is also of interest to those working in signal processing, linear algebra, visual (color/spatial) perception, psychophysics, psychometrics, and statistics.

Author Biography

Jean-Bernard Martens Eindhoven University of Technology, The Netherlands

Table of Contents

1. VISUAL PERCEPTION AND LINEAR SYSTEM THEORY	1	(46)
1 Introduction	1	(1)
2 Linear Systems	2	(1)
3 Electromagnetic Radiation and Radiometry	3	(20)
3.1 Electromagnetic Radiation	4	(2)
3.2 Optics	6	(5)
3.3 Radiometry for a Lens System	11	(6)
3.4 Radiometry for Reflecting Surfaces	17	(6)
4 Color Perception	23	(2)
5 Brightness Matching	25	(7)
5.1 Axioms of Abney	25	(2)
5.2 Spectral Sensitivity Function (SSF)	27	(2)
5.3 Anatomical and Electrophysiological Evidence	29	(3)
6 Color Matching	32	(15)
6.1 Axioms of Grassman	32	(1)
6.2 Color Matching Function (CMF)	33	(3)
6.3 Cone Sensitivities	36	(11)
2. LINEAR SYSTEM THEORY AND VECTOR SPACES	47	(54)
1 Introduction	47	(3)
2 Signals and Vectors	50	(4)
2.1 Vector Spaces	50	(2)
2.2 Linear Functionals and Vector Products	52	(2)
3 Vector Norms and Bauach Spaces	54	(8)
3.1 Norms and Distances	54	(1)
3.2 Cauchy Sequences and Banach Spaces	55	(2)
3.3 Dual Vector Spaces	57	(1)
3.4 Schwartz Functions and Tempered Distributions	58	(2)
3.5 Bases	60	(2)
4 Linear Operators between Banach Spaces	62	(7)
4.1 Linear Operators	62	(1)
4.2 Dual Bases	63	(4)
4.3 Operators and Matrices	67	(2)
5 Vector Lengths and Hilbert Spaces	69	(14)
5.1 Hilbert Spaces	69	(3)
5.2 Bases of Orthogonal Polynomials	72	(6)
5.3 Orthogonal Projection	78	(5)
6 Linear Operators between Hilbert Spaces	83	(18)
6.1 Unitary Operators	83	(1)
6.2 Adjoint Operators	84	(1)
6.3 Eigenvalue Decomposition	85	(1)
6.4 Singular Value Decomposition	86	(1)
6.5 Pseudo-Inverse Operators	87	(2)
6.6 Frames	89	(12)
3. COLOR PERCEPTION AND COLORIMETRY	101	(44)
1 Introduction	101	(1)
2 Fundamental Color Space	102	(8)
2.1 Vector Space Model for Color Matching	102	(2)
2.2 Analysis of Color Matching Data	104	(6)
3 Color Diagram	110	(2)
4 Photometry	112	(11)
4.1 Luminance and Luminance Ratio	112	(2)
4.2 Brightness Models amid Display Standardization	114	(5)
4.3 Brightness Adaptation	119	(4)
5 Colorimetry	123	(22)
5.1 Hering Primaries	123	(2)
5.2 Chromaticity Plane	125	(3)
5.3 CIE Standard Illuminants	128	(2)
5.4 The Munsell Book of Color	130	(1)
5.5 CIELAB Uniform Color Space	131	(14)
4. COLOR MANAGEMENT	145	(48)
1 Introduction	145	(3)
2 Additive Color Displays	148	(12)
2.1 Model	148	(4)
2.2 Display Calibration	152	(8)
3 Multiplicative Color Displays	160	(5)
3.1 Continuous-Tone Printing	160	(3)
3.2 Half-Tone Printing	163	(2)
4 Standardized Color Coordinates	165	(8)
4.1 Standardized Displays	165	(4)
4.2 Color Encoding	169	(4)
4.3 Gamma-Corrected Color Values	173	(1)
5 Image Sensors	173	(7)
5.1 Model	173	(3)
5.2 Sensor Calibration	176	(4)
6 Reproducing Reproductions	180	(2)
7 Color Reproduction and Image Quality	182	(11)
7.1 Gamma Variations	182	(3)
7.2 Quality: Contrast versus Naturalness	185	(8)
5. PSYCHOPHYSICAL MEASUREMENT AND MODELLING OF IMAGE QUALITY	193	(94)
1 Introduction	193	(2)
2 Example of Multidimensional Modelling	195	(6)
3 Psychophysical Measurement	201	(5)
3.1 Psychophysics	201	(2)
3.2 Response Variables and Scales	203	(2)
3.3 Non-Metric Scales and Response Functions	205	(1)
4 Psychophysical Procedures	206	(6)
4.1 Local Psychophysics	207	(1)
4.2 Global Psychophysics	208	(4)
5 Multidimensional Modelling of Image Quality	212	(3)
6 MDS Modelling of Continuous Data	215	(28)
6.1 Maximum-Likelihood (ML) Optimization	216	(12)
6.2 Power-Like Data Transformations	228	(2)
6.3 Non-Metric Data	230	(3)
6.4 Maximum-Likelihood Parameter Estimation	233	(6)
6.5 Graphical User Interface to XGms	239	(4)
7 Examples of Continuous Data Analysis	243	(15)
7.1 Coded Images	243	(9)
7.2 Images with Blur and Noise	252	(6)
8 MDS Modelling of Discrete Data	258	(11)
8.1 Thurstone Modelling of Attribute Data	260	(3)
8.2 ML Optimization for a Single Attribute	263	(1)
8.3 ML Optimization in MDS	264	(3)
8.4 Ordinal Regression and Instrumental Models	267	(1)
8.5 Chi-Squared Statistics	267	(2)
9 Examples of Discrete Data Analysis	269	(3)
9.1 Stimulus Configurations	269	(1)
9.2 Ordinal Regression of Attribute Scores	270	(2)
10 Summary	272	(15)
6. DISCRETE PERIODIC SIGNALS AND FOURIER TRANSFORMATIONS	287	(28)
1 Introduction	287	(1)
2 One-dimensional Signal Transformations	288	(11)
2.1 Periodic and Discrete Signals	289	(2)
2.2 Canonical Basis	291	(2)
2.3 Fourier Basis	293	(1)
2.4 Convolution	294	(2)
2.5 Fourier Transformations and Fourier Series	296	(3)
3 Lattices	299	(3)
3.1 Definitions	299	(2)
3.2 Reciprocal Lattice	301	(1)
4 Multi-dimensional Signal Transformations	302	(13)
4.1 Periodic and Discrete Signals	302	(2)
4.2 Canonical Basis	304	(1)
4.3 Fourier Basis	305	(4)
4.4 Convolution 307
4.5 Fourier Transformations and Fourier Series	309	(6)
7. IMAGE SAMPLING AND INTERPOLATION	315	(36)
1 Introduction	315	(1)
2 Sampling of Periodic Signals	316	(6)
2.1 Sampling with Test Functions	316	(3)
2.2 Dual Basis of a Repetitive Basis	319	(3)
3 Comparing Original and Interpolated Signals	322	(5)
3.1 Quadratic Error Criterium	322	(2)
3.2 Fourier Transformation of an Interpolated Signal	324	(3)
4 Inverse Operators	327	(7)
4.1 Gaussian functions	331	(1)
4.2 B-splines	332	(2)
5 Perceptual Assessment	334	(17)
5.1 Experimental Set-Up	335	(2)
5.2 Experiment 1 - Effect of Interpolation Filter	337	(3)
5.3 Experiment 2 - Effect of Sampling Filter	340	(11)
8. SPATIO-TEMPORAL CHARACTERISTICS OF THE HUMAN VISUAL SYSTEM	351	(36)
1 Introduction	351	(1)
2 Eye - Optical Transfer Function (OTF)	352	(12)
2.1 Optics of the Human Eye	352	(2)
2.2 Small-Angle and Large-Angle OTF	354	(4)
2.3 Wavelength-Dependent OTF	358	(4)
2.4 Color Coordinate Transformations	362	(2)
3 Contrast Sensitivity Function (CSF)	364	(13)
3.1 Detection of Counterphase Gratings	365	(2)
3.2 Detection of Drifting Gratings	367	(3)
3.3 Detection of Static Gratings	370	(4)
3.4 Detection of Colored Gratings	374	(3)
4 CIELAB Extensions	377	(10)
4.1 Asymmetric Color Matching	377	(3)
4.2 S-CIELAB	380	(7)
9. OPTIMIZING SAMPLING STRUCTURES	387	(20)
1 Introduction	387	(1)
2 Sampling Lattice Optimization	388	(8)
2.1 Periodic Structures	388	(1)
2.2 Still Images	389	(6)
2.3 Image Sequences	395	(1)
3 Display Function Optimization	396	(7)
3.1 Display Functions	396	(1)
3.2 Threshold Visibility	397	(1)
3.3 Impairment Model	398	(5)
4 Sampling Function Optimization	403	(4)
10. IMAGE QUANTIZATION	407	(40)
1 Introduction	407	(2)
2 Quantization with Bounded Distortion	409	(6)
2.1 Distortion Measures	409	(3)
2.2 Quantizer Design	412	(1)
2.3 Companding	413	(2)
3 Statistical Quantization	415	(1)
4 Uniform Quantization	416	(6)
4.1 Quantization Error	416	(3)
4.2 Quantizer Output	419	(1)
4.3 Correlated Quantization Errors	420	(2)
5 Dithering	422	(2)
6 Ordered Dithering	424	(6)
7 Noise Dithering	430	(3)
8 Error Diffusion	433	(4)
9 Experimental Comparison	437	(1)
10 Quantization of Color Images	438	(9)
11. DOUBLE-ENDED INSTRUMENTAL MODELS OF IMAGE QUALITY	447	(36)
1 Introduction	447	(4)
2 Instrumental Dissimilarity Measures	451	(19)
2.1 Sarnoff Model	452	(5)
2.2 Simplified Sarnoff Model	457	(3)
2.3 Simple Distance Measures	460	(10)
3 Performance of Double-Ended Measures	470	(10)
3.1 Experimental Data	470	(2)
3.2 Comparison Methods	472	(2)
3.3 Instrumental Measures versus Experimental Data	474	(6)
4 Conclusions	480	(3)
12. SINGLE-ENDED INSTRUMENTAL MODELS OF IMAGE QUALITY	483	(36)
1 Introduction	483	(3)
2 Computational Approach	486	(1)
3 Feature Detection	487	(10)
3.1 Residue Energy	488	(1)
3.2 Energy and Amplitude Histograms	488	(6)
3.3 Energy Maxima	494	(3)
4 Edge Parameter Estimation	497	(9)
4.1 Two-Dimensional Hermite Transformation	498	(1)
4.2 One-Dimensional Hermite Transformation	499	(1)
4.3 Composite Edges	499	(5)
4.4 Summary Model	504	(2)
5 Images with Correlated Noise	506	(3)
6 Images with Noise and Blur	509	(2)
7 JPEG-Coded Images	511	(3)
8 Conclusions	514	(5)
References	519	(20)
Index	539