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Camera Image Quality Benchmarking1149
The essential guide to the entire process behind performing a complete characterization and benchmarking of cameras through image quality analysis Camera Image Quality Benchmarking contains the basic information and approaches for the use of subjectively correlated image quality metrics and outlines a framework for camera benchmarking. The authors show how to quantitatively compare image quality of cameras used for consumer photography. This book helps to fill a void in the literature by detailing the types of objective and subjective metrics that are fundamental to benchmarking still and video imaging devices. Specifically, the book provides an explanation of individual image quality attributes and how they manifest themselves to camera components and explores the key photographic still and video image quality metrics. The text also includes illustrative examples of benchmarking methods so that the practitioner can design a methodology appropriate to the photographic usage in consideration. The authors outline the various techniques used to correlate the measurement results from the objective methods with subjective results. The text also contains a detailed description on how to set up an image quality characterization lab, with examples where the methodological benchmarking approach described has been implemented successfully. This vital resource: Explains in detail the entire process behind performing a complete characterization and benchmarking of cameras through image quality analysis Provides best practice measurement protocols and methodologies, so readers can develop and define their own camera benchmarking system to industry standards Includes many photographic images and diagrammatical illustrations to clearly convey image quality concepts Champions benchmarking approaches that value the importance of perceptually correlated image quality metrics Written for image scientists, engineers, or managers involved in image quality and evaluating camera performance, Camera Image Quality Benchmarking combines knowledge from many different engineering fields, correlating objective (perception-independent) image quality with subjective (perception-dependent) image quality metrics.
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JONATHAN B. PHILLIPS, is a Staff Image Scientist at Google, USA. He is a United States delegate to the technical committee ISO/TC 42 Photography and a major contributor to the IEEE Camera Phone Image Quality (CPIQ) initiative. HENRIK ELIASSON, PHD, is an image sensor and image analysis specialist at Eclipse Optics, Sweden. He is a senior member of SPIE.
Preface i List of Abbreviations 1 1 Introduction 5 1.1 Image Content and Image Quality 6 1.2 Benchmarking 23 1.3 Book Content 28 2 Defining Image Quality 33 2.1 What is Image Quality? 33 2.2 Image Quality Attributes 36 2.3 Subjective and Objective Image Quality Assessment 38 3 Image Quality Attributes 41 3.1 Global attributes 41 3.2 Local attributes 51 3.3 Video Quality Attributes 63 4 The Camera 71 4.1 The Pinhole Camera 71 4.2 Lens 73 4.3 Image Sensor 84 4.4 Image Signal Processor 102 4.5 Illumination 115 4.6 Video Processing 116 4.7 System Considerations 125 5 Subjective Image Quality Assessment Theory and Practice 129 5.1 Psychophysics 130 5.2 Measurement Scales 131 5.3 Psychophysical Methodologies 134 5.4 Cross-Modal Psychophysics 139 5.5 Thurstonian Scaling 143 5.6 Quality Ruler 146 5.7 Subjective Video Quality 165 6 Objective Image Quality Assessment Theory and Practice 185 6.1 Exposure and Tone 186 6.2 Dynamic Range 189 6.3 Color 189 6.4 Shading 201 6.5 Geometric Distortion 202 6.6 Stray Light 205 6.7 Sharpness and Resolution 207 6.8 Texture Blur 228 6.9 Noise 232 6.10 Color Fringing 238 6.11 Image Defects 239 6.12 Video Quality Metrics 240 6.13 Related International Standards 244 7 Perceptually Correlated Image Quality Metrics 251 7.1 Aspects of Human Vision 251 7.2 HVS Modeling 256 7.3 Viewing Conditions 257 7.4 Spatial Image Quality Metrics 259 7.5 Color 270 7.6 Other Metrics 278 7.7 Combination of Metrics 279 7.8 Full-Reference Digital Video Quality Metrics 279 8 Measurement Protocols Building Up a Lab 301 8.1 Still Objective Measurements 301 8.2 Video Objective Measurements 321 8.3 Still Subjective Measurements 325 8.4 Video Subjective Measurements 333 9 The Camera Benchmark Process 337 9.1 Objective Metrics for Benchmarking 337 9.2 Subjective Methods for Benchmarking 340 9.3 Methods of Combining Metrics 344 9.4 Benchmark Systems 346 9.5 Example Benchmark Results 353 9.6 Benchmarking Validation 375 10 Summary and Conclusions 383 Index 389