High Dynamic Range Video

From Acquisition, to Display and Applications
 
 
Academic Press
  • 1. Auflage
  • |
  • erschienen am 27. April 2016
  • |
  • 630 Seiten
 
E-Book | ePUB mit Adobe DRM | Systemvoraussetzungen
E-Book | PDF mit Adobe DRM | Systemvoraussetzungen
E-Book | ePUB mit Adobe DRM | Systemvoraussetzungen
978-0-12-803039-4 (ISBN)
 

At the time of rapid technological progress and uptake of High Dynamic Range (HDR) video content in numerous sectors, this book provides an overview of the key supporting technologies, discusses the effectiveness of various techniques, reviews the initial standardization efforts and explores new research directions in all aspects involved in HDR video systems.

Topics addressed include content acquisition and production, tone mapping and inverse tone mapping operators, coding, quality of experience, and display technologies. This book also explores a number of applications using HDR video technologies in the automotive industry, medical imaging, spacecraft imaging, driving simulation and watermarking.

By covering general to advanced topics, along with a broad and deep analysis, this book is suitable for both the researcher new or familiar to the area.

With this book the reader will:

    • Gain a broad understanding of all the elements in the HDR video processing chain
    • Learn the most recent results of ongoing research
    • Understand the challenges and perspectives for HDR video technologies

    • Covers a broad range of topics encompassing the whole processing chain in HDR video systems, from acquisition to display
    • Provides a comprehensive overview of this fast emerging topic
    • Presents upcoming applications taking advantages of HDR
    • Englisch
    • London
    Elsevier Science
    • 50,79 MB
    978-0-12-803039-4 (9780128030394)
    0128030399 (0128030399)
    weitere Ausgaben werden ermittelt
    • Front Cover
    • High Dynamic Range Video: From Acquisition to Display and Applications
    • Copyright
    • Contents
    • Contributors
    • Editor Biographies
    • Preface
    • Acknowledgments
    • Chapter 1: The Fundamental basis of HDR: Comparametric Equations
    • 1.1 Introduction to High Dynamic Range Imaging
    • 1.1.1 The Fundamental Concept of HDR Sensing and Metasensing
    • 1.1.2 The Fundamental Principle of HDR: Dynamic Range and Dynamage Range
    • 1.1.3 HDR Imaging Techniques
    • 1.1.4 HDR From Multiple Exposures
    • 1.2 Historical Motivation for HDR Imaging
    • 1.3 Theory of HDR Imaging
    • 1.3.1 The Wyckoff Principle and the Range of Light
    • 1.3.2 What's Good for the Domain Is Good for the Range
    • 1.3.3 Extending Dynamic Range and Improvement of Range Resolution by Combining Differently Exposed Pictures of the Same S ...
    • 1.3.4 The Photoquantity, q
    • 1.3.5 The Camera as an Array of Light Meters
    • 1.3.6 The Accidentally Discovered Compander
    • 1.3.7 Why Stockham Was Wrong
    • 1.3.8 The Value of Doing the Exact Opposite of What Stockham Advocated
    • 1.3.9 Using Differently Exposed Pictures of the Same Subject Matter to Get a Better Estimate of q
    • 1.3.10 Exposure Interpolation and Extrapolation
    • 1.4 Comparametric Image Processing: Comparing Differently Exposed Images of the Same Subject Matter
    • 1.4.1 Misconceptions About Gamma Correction
    • 1.4.2 Comparametric Plots and Comparametric Equations
    • 1.4.3 Zeta Correction of Images
    • 1.4.4 The Affine Comparametric Equation and Affine Correction of Images
    • 1.4.5 The Preferred Correction of Images
    • 1.4.6 Some Solutions to Some Comparametric Equations That Are Particularly Illustrative or Useful
    • 1.4.7 Properties of Comparametric Equations
    • 1.5 Practical Implementations
    • 1.5.1 Comparing Two Images That Differ Only in Exposure
    • 1.5.2 Joint Histograms and Comparagrams
    • 1.5.3 Comparametric Regression and the Joint Histogram
    • 1.5.4 Comparametric Regression to a Straight Line
    • 1.5.5 Comparametric Regression to the Preferred Model
    • 1.6 Tone Mapping in HDR Systems
    • 1.6.1 An Extreme Example With Spatiotonal Processing of Photoquantities
    • 1.7 Analytical Solution of Comparametric Equations
    • 1.7.1 Overview
    • 1.7.2 Formal Solution by Scaling Operator
    • 1.7.3 Solution by Ordinary Differential Equation
    • 1.8 Compositing as Bayesian Joint Estimation
    • Pairwise estimation
    • Alternative graph topology
    • Constructing the CCRF
    • Incremental updates
    • 1.8.1 Example Joint Estimator
    • 1.8.1.1 Bayesian probabilistic model for the CCRF
    • 1.8.2 Discussion Regarding Compositing via the CCRF
    • 1.8.3 Review of Analytical Comparametric Equations
    • 1.9 Efficient Implementation of HDR Reconstruction Via CCRF Compression
    • Quadtree representation
    • Reducing the quadtree
    • Error weighting and tree depth criteria
    • Corner value access
    • 1.9.1 Implementation
    • 1.9.1.1 Addressing circuit
    • 1.9.1.2 Interpolation circuit
    • 1.9.2 Compression Performance
    • 1.9.2.1 Hardware resource usage
    • 1.9.3 Conclusion
    • Acknowledgments
    • References
    • Part I: Content Acquisition and Production
    • Chapter 2: Unified Reconstruction of Raw HDR Video Data
    • 2.1 Introduction
    • 2.1.1 Outline
    • 2.2 Optical Design for HDR Video Capture
    • 2.2.1 Multisensor Systems
    • 2.2.2 Spatially Varying Sensor Exposure
    • 2.3 Image Formation Model
    • 2.3.1 Sensor Noise Model
    • 2.3.2 Variance Estimate
    • 2.3.2.1 Parameter calibration
    • 2.4 HDR Reconstruction
    • 2.4.1 Local Polynomial Model
    • 2.4.2 Maximum Localized Likelihood Fitting
    • 2.4.3 Parameters
    • 2.4.3.1 Window and scale selection
    • 2.4.4 Adaptive LPA Reconstruction
    • 2.4.5 Color Channel Correlation
    • 2.5 Example Applications
    • 2.5.1 Multisensor HDR Video Capture
    • 2.5.2 Spatial Multiplexing Using Dual-ISO Capture
    • 2.6 Conclusion
    • References
    • Chapter 3: Stack-Based Algorithms for HDR Capture and Reconstruction
    • 3.1 Introduction
    • 3.2 Metering for HDR Imaging
    • 3.2.1 Range-Agnostic Methods
    • 3.2.2 Range-Aware Methods
    • 3.2.3 Noise-Aware Methods
    • 3.3 From LDR to HDR
    • 3.3.1 Radiometric Calibration
    • 3.3.1.1 Parametric methods for radiometric calibration
    • 3.3.1.2 Nonparametric methods for radiometric calibration
    • 3.3.1.3 Single-image methods for radiometric calibration
    • 3.3.2 Merging Multiple LDR Images Into the Final HDR Result
    • 3.3.2.1 Maximum likelihood estimation
    • 3.3.2.2 Winner-take-all merging schemes
    • 3.3.2.3 Exposure fusion methods
    • 3.4 Handling Artifacts From Motion During HDR Reconstruction
    • 3.4.1 Simple Rigid-Alignment Methods
    • 3.4.2 Rejection Algorithms for HDR Deghosting
    • 3.4.2.1 Rejection methods without a reference image
    • 3.4.2.2 Reference-based rejection methods
    • 3.4.3 Nonrigid Registration Algorithms for HDR Deghosting
    • 3.4.3.1 Optical flow and correspondence registration methods
    • 3.4.3.2 Patch-based synthesis methods
    • 3.5 Conclusion
    • Acknowledgments
    • References
    • Chapter 4: Multiview HDR Video Sequence Generation
    • 4.1 Introduction
    • 4.2 HDR and Stereo HDR Video Acquisition
    • 4.2.1 Temporal Considerations
    • 4.2.2 Spatial Considerations
    • 4.2.2.1 Camera versus scene movement
    • 4.2.2.2 Local and/or global misalignment
    • 4.2.2.3 Generated HDR content
    • 4.3 Free-Path Single Camera
    • 4.3.1 Multiexposure Acquisition Setup
    • 4.3.2 Per-Frame HDR Video Generation
    • 4.4 Multiscopic HDR Video
    • 4.4.1 Stereoscopic Imaging
    • 4.4.2 Epipolar Geometry
    • 4.4.3 Multiple-Exposure Stereo Matching
    • 4.4.3.1 Problem formulation
    • 4.4.3.2 Per frame CRF recovery methods
    • 4.4.3.3 Offline CRF recovery methods
    • 4.5 Conclusions
    • References
    • Chapter 5: HDR, Cinematography, and Stereoscopy
    • 5.1 Introduction
    • 5.2 Experiments With the HDR Technique
    • 5.2.1 Exposures
    • 5.2.2 Cameras
    • 5.2.3 Lenses
    • 5.2.4 Filters
    • 5.2.5 Rig
    • 5.2.6 Exposure Time for Images
    • 5.2.7 Preparation for Shooting
    • 5.2.8 Selection of the Location
    • 5.2.9 Shooting
    • 5.3 Postproduction
    • 5.3.1 Issues Related to Double Exposure
    • 5.3.2 Linearization
    • 5.3.3 Corrections
    • 5.3.4 Geometric Corrections
    • 5.3.5 Colorimetric Corrections
    • 5.3.6 Fusion
    • 5.3.7 Examples
    • 5.4 HDR: Enhanced Artistic Palette Available for Directors of Photography and Directors
    • Acknowledgments
    • Part II: Processing
    • Chapter 6: Video Tone Mapping
    • 6.1 Temporal Artifacts
    • 6.1.1 Global Flickering Artifacts
    • 6.1.2 Local Flickering Artifacts
    • 6.1.3 Temporal Noise
    • 6.1.4 Temporal Brightness Incoherency
    • 6.1.5 Temporal Object Incoherency
    • 6.1.6 Temporal Hue Incoherency
    • 6.2 Video TMOs
    • 6.2.1 Global Temporal Filtering
    • 6.2.2 Local Temporal Filtering
    • 6.2.3 Iterative Filtering
    • 6.3 Temporal Artifacts Caused by Video TMOs
    • 6.3.1 Temporal Contrast Adaptation
    • 6.3.2 Ghosting Artifacts
    • 6.4 Recent Video TMOs
    • 6.4.1 Zonal Brightness Coherency
    • 6.4.2 Temporally Coherent Local Tone Mapping
    • 6.5 Summary
    • References
    • Chapter 7: Evaluation of Tone Mapping Operators for HDR Video
    • 7.1 Introduction
    • 7.2 Subjective Quality Assessment Method
    • 7.2.1 TMO Intent
    • 7.2.2 Evaluation Method
    • 7.2.3 Parameter Settings
    • 7.2.4 Input Material
    • 7.2.5 Experimental Setup
    • 7.3 Survey of TMO Evaluation Studies
    • 7.4 Evaluation Studies for Video TMOs
    • 7.5 Video TMO Evaluation Study I
    • 7.5.1 TMO Intent
    • 7.5.2 Parameter Settings
    • 7.5.3 S-Shaped Curve Performance
    • 7.6 Video TMO Evaluation Study II
    • 7.6.1 TMO Selection
    • 7.6.2 Parameter Selection Experiment
    • 7.6.3 Qualitative Evaluation Experiment
    • 7.6.4 Pairwise Comparison Experiment
    • 7.6.5 Conclusion
    • 7.7 Summary
    • References
    • Chapter 8: Using Simulated Visual Illusions and Perceptual Anomalies to Convey Dynamic Range
    • 8.1 Introduction
    • 8.1.1 Principle
    • 8.1.2 Outline
    • 8.1.3 Artistic Practice
    • 8.1.4 Technical Background
    • 8.2 Three-Dimensional Unsharp Masking
    • 8.2.1 The Cornsweet Illusion
    • 8.2.2 Definition
    • 8.2.3 Contrast Signal Calculation
    • 8.2.3.1 GPU implementation
    • 8.2.3.2 Coherence of the contrast signal
    • 8.2.4 Results
    • 8.2.5 Related Work
    • 8.2.6 Discussion
    • 8.3 Temporal Glare
    • 8.3.1 A Dynamic Human Eye Model for Glare
    • 8.3.1.1 Cornea
    • 8.3.1.2 Iris and pupil
    • 8.3.1.3 Lens
    • 8.3.1.4 Vitreous humor
    • 8.3.1.5 Retina
    • 8.3.1.6 Eyelashes and blinking
    • 8.3.2 Wave Optics Simulation of Light Scattering
    • 8.3.3 Implementation
    • 8.3.4 Human Aperture Model
    • 8.3.5 Fresnel Diffraction
    • 8.3.6 Chromatic Blur
    • 8.3.7 Convolution
    • 8.3.8 Results
    • 8.3.9 Related Work
    • 8.4 Afterimages
    • 8.4.1 Introduction
    • 8.4.2 Approach
    • 8.4.2.1 Model
    • 8.4.3 Eye Radiance and Dynamics
    • 8.4.4 Retinal and Effective Radiance
    • 8.4.5 Retinal Kinetics
    • 8.4.6 Solver
    • 8.4.7 Diffusion
    • 8.4.8 Chromatic Effect
    • 8.4.8.1 LDR compensation
    • 8.4.8.2 Flight of colors
    • 8.4.8.3 Implementation
    • 8.4.9 Result
    • 8.4.10 Simulation Scenario
    • 8.4.11 HDR Photo Viewer Scenario
    • 8.4.12 Game Scenario
    • 8.4.13 Related Work
    • 8.4.14 Afterimages
    • 8.4.15 Visual Computing
    • 8.5 Conclusion
    • 8.5.1 Common Limitations
    • 8.5.2 Extensions
    • 8.5.3 Outlook
    • References
    • Chapter 9: Color Management in HDR Imaging
    • 9.1 Introduction
    • 9.1.1 Flow of Processing
    • 9.1.2 Color Management
    • 9.2 Background
    • 9.2.1 Color
    • 9.2.2 Color Spaces and Color Gamuts
    • 9.2.3 Appearance Correlates and Color Appearance Models
    • 9.3 Color Spaces for HDR and Color Workflows
    • 9.3.1 Perceptual Color Spaces
    • 9.3.2 Perceptual HDR Color Spaces
    • 9.3.3 Display-Referred Color Spaces and Encodings
    • 9.3.4 Postproduction Workflows for HDR
    • 9.4 Color Correction
    • 9.5 Recovery of Clipped and Overexposed Regions
    • 9.5.1 Correction During Acquisition
    • 9.5.2 Inpainting-Based Correction
    • 9.5.3 Neighborhood-Based Correction
    • 9.5.4 Correlation-Based Correction
    • 9.5.5 Color Statistics-Based Correction
    • 9.6 Color Appearance Modeling for HDR
    • 9.6.1 Color Appearance
    • 9.6.2 Measurements and Datasets
    • 9.6.3 Color Appearance Models
    • 9.6.4 Image Appearance Models
    • 9.6.5 HDR Color and Image Appearance Models
    • 9.6.6 Visual Quality
    • 9.6.7 Color Appearance Models in Practice
    • 9.7 Conclusions
    • References
    • Part III: Representation and Coding
    • Chapter 10: High Dynamic Range Video Compression
    • 10.1 Introduction
    • 10.2 HDR Image Storage Formats and Compression
    • 10.3 HDR Video Compression
    • 10.3.1 Layered (Backward-Compatible) HDR Video Compression
    • 10.3.2 High-Bit-Depth (Native) HDR Video Compression
    • 10.4 Summary
    • References
    • Chapter 11: High Dynamic Range and Wide Color Gamut Video Standardization - Status and Perspectives
    • 11.1 Introduction
    • 11.2 HDR and WCG Video Workflows and Related Standardization Activities
    • 11.2.1 The HDR and WCG Video Workflows
    • 11.2.2 Related Standardization Activities
    • 11.3 HDR and WCG in Already Existing Standards
    • 11.3.1 HDR and WCG Video Representation
    • 11.3.2 Metadata for Content Adaptation
    • 11.3.2.1 Application example 1: CRI with WCG content
    • 11.3.2.2 Application example 2: CRI with HDR content
    • 11.3.3 HEVC Coding Tools - Bit Depth and Color Gamut Scalability
    • 11.3.3.1 CGS performance with WCG content
    • 11.3.3.2 CGS performance with HDR and WCG content
    • 11.4 Other Technical Solutions
    • 11.4.1 Alternative OETFs
    • 11.4.2 Alternative Coding Technologies
    • 11.5 Conclusion
    • References
    • Chapter 12: High Dynamic Range Imaging With JPEG XT
    • 12.1 The JPEG XT Standard
    • 12.2 Problem Definition
    • 12.3 The History of JPEG XT
    • 12.4 Coding Technology
    • 12.4.1 IDR Coding
    • 12.4.2 Enlarging the Color Gamut
    • 12.4.3 From IDR to HDR: HDR Coding
    • 12.5 Hardware Implementation
    • 12.6 Coding Performance
    • 12.6.1 IDR Coding Performance
    • 12.6.2 Coding Performance on HDR Images
    • 12.7 Conclusions
    • References
    • Part IV: Display
    • Chapter 13: HDR Display Characterization and Modeling
    • 13.1 Introduction
    • 13.2 HDR Image Display With LED Backlight
    • 13.2.1 Physical Characterization
    • 13.2.2 Display Architectures
    • 13.2.3 Evaluating Distortion
    • 13.3 Optimizing Local Dimming of LED Backlight for Image Display
    • 13.3.1 Local Dimming of LED Backlight
    • 13.3.2 Liquid Crystal Pixel Compensation
    • 13.3.3 Distortion of Backlight Images and Optimizing the Backlight Values
    • 13.4 LED-Backlit 3D Video Displays
    • 13.4.1 Liquid Crystal Pixel Compensation
    • 13.4.2 Formulation of Optimal Backlight Modulation
    • 13.5 Modeling and Evaluation of Display Quality
    • 13.5.1 Necessity of a Display Model for Evaluation of Local Backlight Dimming
    • 13.5.2 Key Points of the Backlight Model
    • 13.5.2.1 Leakage modeling
    • 13.5.2.2 Leakage dependence on the viewing angle
    • 13.6 Concluding Remarks
    • References
    • Chapter 14: Dual Modulation for LED-Backlit HDR Displays
    • 14.1 Introduction
    • 14.2 Dual Modulation for Backlight Dimming
    • 14.3 Proposed Method for Dual Modulation
    • 14.4 Assessing the Performance of a Dual Modulation Algorithm
    • 14.5 Some Practical Lessons for HDR Content Rendering
    • 14.6 Concluding Remarks and Perspectives
    • References
    • Part V: Perception and Quality of Experience
    • Chapter 15: Perceptual Design for High Dynamic Range Systems
    • 15.1 Introduction
    • 15.2 Luminance and Contrast Perception of the HVS
    • 15.2.1 Real-World Luminance and the HVS
    • 15.2.2 Steady-State Dynamic Range
    • 15.2.3 Still Image Studies
    • 15.2.4 Dynamic Range Study Relevant for Moving Imagery
    • 15.3 Quantization and Tone Curve Reproduction
    • 15.3.1 Performance of the PQ EOTF
    • 15.4 Perception of Reflectances, Diffuse White, and Highlights
    • 15.5 Adding Color - Color Gamuts and Color Volumes
    • 15.5.1 Visible Colors and Spectral Locus
    • 15.5.2 Chromaticity and Color Spaces
    • 15.5.3 Color Temperature and Correlated Color Temperature
    • 15.5.4 Colorimetric Color Volume
    • 15.5.5 The Concept of Color Appearance Modeling
    • 15.5.6 Limitations of Perceptually Based Manipulation of Imagery
    • 15.6 Summary
    • References
    • Chapter 16: Quality of Experience and HDR: Concepts and How to Measure It
    • 16.1 Introduction
    • 16.2 Dimensions in HDR QoE
    • 16.3 Measuring HDR QoE: A Few Considerations
    • 16.3.1 Effect of Display
    • 16.3.2 High Luminance Conditions and Visual Discomfort
    • 16.3.3 Observers
    • 16.3.4 Viewing Conditions
    • 16.3.5 Source Content Selection
    • 16.3.6 Paired Comparison Tests in an HDR Setting
    • 16.4 Impact of Tone Mapping Operators on QoE Dimensions
    • 16.4.1 Effect on Perceptual Fidelity
    • 16.4.2 Visual Attention Modification
    • 16.4.3 Impact on Other Aspects
    • 16.5 Case Study: Quality Assessment of Dynamic Range Expansion of Video Sequences
    • 16.5.1 Source LDR Content and Expansion Operators Considered
    • 16.5.2 Display, Test Environment, and Viewing Conditions
    • 16.5.3 Test Method
    • 16.5.4 Results and Discussion
    • 16.6 Concluding Remarks and Perspectives
    • References
    • Chapter 17: HDR Image and Video Quality Prediction
    • 17.1 Introduction
    • 17.2 Approaches for Assessing HDR Fidelity
    • 17.2.1 HVS-Based Models for HDR Quality Measurement
    • 17.2.2 Adaptation of LDR Metrics for Measuring HDR Quality
    • 17.3 From Spatial Frequency Errors to Global Quality Measure of HDR Content: Improvement of the HVS-Based Model
    • 17.3.1 Cross-Validation Results and Analysis
    • 17.4 Adapted LDR Metrics for Measuring HDR Image Quality in the Context of Compression
    • 17.4.1 Metrics and Adaptation
    • 17.4.2 Dataset Description
    • 17.4.3 Results and Analysis
    • 17.5 Tone Mapping and Dynamic Range-Independent Metrics
    • 17.6 Extensions to Video
    • 17.6.1 Brief Description of HDR-VQM
    • 17.6.2 Prediction Performance Comparison
    • 17.7 Concluding Remarks
    • References
    • Part VI: Applications
    • Chapter 18: HDR Imaging in Automotive Applications
    • 18.1 History and Motivation for High Dynamic Range Sensors and Cameras
    • 18.2 Requirements for Automotive Camera Sensors
    • 18.2.1 The Illumination Condition
    • 18.2.2 The Object Reflectance
    • 18.2.3 The Medium Between the Object and the Image
    • 18.2.4 Functional Performance
    • 18.2.5 Operating Range
    • 18.2.6 Reliability
    • 18.2.7 Power Considerations
    • 18.2.8 Cost or the Democratization of a New Technology
    • 18.2.9 Safety
    • 18.3 HDR Implementations
    • 18.3.1 Intrinsic HDR Solutions
    • 18.3.2 Reconstructed HDR Solutions
    • 18.4 HDR Video-Based Driver Assistance Applications
    • 18.4.1 Night Vision
    • 18.4.2 From Lane Detection to Lane Keeping Support
    • 18.4.3 Traffic Sign Recognition to Sign Reading
    • 18.4.4 Headlamp Control
    • 18.4.5 From Rear View to Autonomous Parking
    • 18.4.6 From Object Detection to Preemergency Braking
    • 18.4.7 Autonomous Driving
    • 18.4.8 What Is the Drawback of HDR Imaging?
    • Acknowledgments
    • References
    • Chapter 19: An Application of HDR in Medical Imaging
    • 19.1 Introduction
    • 19.2 Requirements of HDR Visualization in the Medical Field
    • 19.2.1 General Requirements for Medical Imaging Displays
    • 19.2.2 The Added Value of HDR Displays in Specific Medical Applications
    • 19.2.3 Gray Level Mapping in HDR Medical Images
    • 19.3 Evaluation of Medical HDR Displays
    • 19.3.1 Luminance
    • 19.3.2 Uniformity
    • 19.3.3 Grayscale Tracking
    • 19.3.4 Spatial Noise and Resolution
    • 19.3.5 Temporal Response
    • 19.3.6 Veiling Glare
    • 19.3.7 Quantization
    • 19.4 The Dual-Layer Approach
    • 19.4.1 Image Splitting and the Problem of the Parallax Error
    • 19.4.2 Techniques for Image Splitting
    • 19.4.3 Development of an HDR Display Function
    • 19.4.4 A Dual-Layer LCD Prototype
    • 19.5 Conclusions
    • Acknowledgments
    • References
    • Chapter 20: High Dynamic Range Digital Imaging of Spacecraft
    • 20.1 Introduction
    • 20.2 Background
    • 20.2.1 An Engineering Imagery Example
    • 20.3 Film Baseline
    • 20.3.1 Dynamic Range of Film
    • 20.3.2 Autoexposure and Contrast Ratio
    • 20.3.3 Linear and Nonlinear Quantization
    • 20.3.4 Playback and Display
    • 20.3.5 Summary of Film Use
    • 20.4 HDR Imaging of Spacecraft Field Experiments
    • 20.4.1 High Definition Camera Test During STS-129
    • 20.4.2 RED ONE M Camera Test During STS-131
    • 20.4.3 HDR Imaging During the Final Space Shuttle Flight STS-135
    • 20.4.3.1 RED ONE M test STS-135
    • 20.4.3.2 ARRI Alexa test
    • 20.4.3.3 RED EPIC test
    • 20.4.3.4 Photron SA2 test
    • 20.4.3.5 Cooke DiMax test
    • 20.4.3.6 Vision Research Phantom HD Gold test
    • 20.4.4 RED EPIC HDR Mode During Delta 4 WGS 5
    • 20.4.5 Review of HDR Field Experiments
    • 20.4.5.1 State of technology
    • 20.4.5.2 Digital formats
    • 20.4.5.3 Benefits and trade-offs
    • 20.5 Calibrated Measurement of Imager Dynamic Range
    • 20.6 HDR Workflow and Display Device Luminance
    • 20.7 Conclusions
    • Acknowledgments
    • References
    • Chapter 21: The Dynamic Range of Driving Simulation
    • 21.1 Introduction
    • 21.2 No Need for HDR Video in Driving Simulations?
    • 21.3 Visual Factors Which Impact Driving Behavior
    • 21.4 HDR Rendering
    • 21.5 Photometric Control of CG Images in Driving Simulations
    • 21.6 Conclusion
    • References
    • Chapter 22: HDR Image Watermarking
    • 22.1 A Brief Introduction to Digital Watermarking
    • 22.1.1 Digital Watermarking Requirements
    • 22.1.2 Watermarking System Examples
    • 22.1.3 Structure of a Watermarking System
    • 22.1.3.1 Watermark embedding
    • 22.1.3.2 Watermark channel
    • 22.1.3.3 Watermark recovery
    • 22.1.4 Watermarking System Evaluation
    • 22.2 Digital Watermarking for HDR Images
    • 22.2.1 Requirements for HDR Image Watermarking
    • 22.2.2 Survey of the Current State of the Art
    • 22.2.3 Summary of HDR Image Watermarking Systems
    • 22.3 Concluding Remarks
    • References
    • Index
    • Back Cover

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