High Dynamic Range Video

From Acquisition, to Display and Applications

1st Edition - April 4, 2016
Imprint: Academic Press
Editors: Frédéric Dufaux, Patrick Le Callet, Rafal Mantiuk, Marta Mrak
Language: English
Hardback ISBN:
9 7 8 - 0 - 0 8 - 1 0 0 4 1 2 - 8
eBook ISBN:
9 7 8 - 0 - 1 2 - 8 0 3 0 3 9 - 4

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 technolog… Read more

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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

Editor Biographies
Preface
Acknowledgments
Chapter 1: The Fundamental Basis of HDR: Comparametric Equations
- Abstract
- Acknowledgments
- 1.1 Introduction to High Dynamic Range Imaging
- 1.2 Historical Motivation for HDR Imaging
- 1.3 Theory of HDR Imaging
- 1.4 Comparametric Image Processing: Comparing Differently Exposed Images of the Same Subject Matter
- 1.5 Practical Implementations
- 1.6 Tone Mapping in HDR Systems
- 1.7 Analytical Solution of Comparametric Equations
- 1.8 Compositing as Bayesian Joint Estimation
- 1.9 Efficient Implementation of HDR Reconstruction via CCRF Compression
Part I: Content Acquisition and Production
- Chapter 2: Unified Reconstruction of Raw HDR Video Data
  - Abstract
  - 2.1 Introduction
  - 2.2 Optical Design for HDR Video Capture
  - 2.3 Image Formation Model
  - 2.4 HDR Reconstruction
  - 2.5 Example Applications
  - 2.6 Conclusion
- Chapter 3: Stack-Based Algorithms for HDR Capture and Reconstruction
  - Abstract
  - Acknowledgments
  - 3.1 Introduction
  - 3.2 Metering for HDR Imaging
  - 3.3 From LDR to HDR
  - 3.4 Handling Artifacts From Motion During HDR Reconstruction
  - 3.5 Conclusion
- Chapter 4: Multiview HDR Video Sequence Generation
  - Abstract
  - 4.1 Introduction
  - 4.2 HDR and Stereo HDR Video Acquisition
  - 4.3 Free-Path Single Camera
  - 4.4 Multiscopic HDR Video
  - 4.5 Conclusions
- Chapter 5: HDR, Cinematography, and Stereoscopy
  - Abstract
  - Acknowledgments
  - 5.1 Introduction
  - 5.2 Experiments With the HDR Technique
  - 5.3 Postproduction
  - 5.4 HDR: Enhanced Artistic Palette Available for Directors of Photography and Directors
Part II: Processing
- Chapter 6: Video Tone Mapping
  - Abstract
  - 6.1 Temporal Artifacts
  - 6.2 Video TMOs
  - 6.3 Temporal Artifacts Caused by Video TMOs
  - 6.4 Recent Video TMOs
  - 6.5 Summary
- Chapter 7: Evaluation of Tone Mapping Operators for HDR Video
  - Abstract
  - 7.1 Introduction
  - 7.2 Subjective Quality Assessment Method
  - 7.3 Survey of TMO Evaluation Studies
  - 7.4 Evaluation Studies for Video TMOs
  - 7.5 Video TMO Evaluation Study I
  - 7.6 Video TMO Evaluation Study II
  - 7.7 Summary
- Chapter 8: Using Simulated Visual Illusions and Perceptual Anomalies to Convey Dynamic Range
  - Abstract
  - 8.1 Introduction
  - 8.2 Three-Dimensional Unsharp Masking
  - 8.3 Temporal Glare
  - 8.4 Afterimages
  - 8.5 Conclusion
- Chapter 9: Color Management in HDR Imaging
  - Abstract
  - 9.1 Introduction
  - 9.2 Background
  - 9.3 Color Spaces for HDR and Color Workflows
  - 9.4 Color Correction
  - 9.5 Recovery of Clipped and Overexposed Regions
  - 9.6 Color Appearance Modeling for HDR
  - 9.7 Conclusions
Part III: Representation and Coding
- Chapter 10: High Dynamic Range Video Compression
  - Abstract
  - 10.1 Introduction
  - 10.2 HDR Image Storage Formats and Compression
  - 10.3 HDR Video Compression
  - 10.4 Summary
- Chapter 11: High Dynamic Range and Wide Color Gamut Video Standardization — Status and Perspectives
  - Abstract
  - 11.1 Introduction
  - 11.2 HDR and WCG Video Workflows and Related Standardization Activities
  - 11.3 HDR and WCG in Already Existing Standards
  - 11.4 Other Technical Solutions
  - 11.5 Conclusion
- Chapter 12: High Dynamic Range Imaging with JPEG XT
  - Abstract
  - 12.1 The JPEG XT Standard
  - 12.2 Problem Definition
  - 12.3 The History of JPEG XT
  - 12.4 Coding Technology
  - 12.5 Hardware Implementation
  - 12.6 Coding Performance
  - 12.7 Conclusions
Part IV: Display
- Chapter 13: HDR Display Characterization and Modeling
  - Abstract
  - 13.1 Introduction
  - 13.2 HDR Image Display With LED Backlight
  - 13.3 Optimizing Local Dimming of LED Backlight for Image Display
  - 13.4 LED-Backlit 3D Video Displays
  - 13.5 Modeling and Evaluation of Display Quality
  - 13.6 Concluding Remarks
- Chapter 14: Dual Modulation for LED-Backlit HDR Displays
  - Abstract
  - 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
Part V: Perception and Quality of Experience
- Chapter 15: Perceptual Design for High Dynamic Range Systems
  - Abstract
  - 15.1 Introduction
  - 15.2 Luminance and Contrast Perception of the HVS
  - 15.3 Quantization and Tone Curve Reproduction
  - 15.4 Perception of Reflectances, Diffuse White, and Highlights
  - 15.5 Adding Color — Color Gamuts and Color Volumes
  - 15.6 Summary
- Chapter 16: Quality of Experience and HDR: Concepts and How to Measure It
  - Abstract
  - 16.1 Introduction
  - 16.2 Dimensions in HDR QoE
  - 16.3 Measuring HDR QoE: A Few Considerations
  - 16.4 Impact of Tone Mapping Operators on QoE Dimensions
  - 16.5 Case Study: Quality Assessment of Dynamic Range Expansion of Video Sequences
  - 16.6 Concluding Remarks and Perspectives
- Chapter 17: HDR Image and Video Quality Prediction
  - Abstract
  - 17.1 Introduction
  - 17.2 Approaches for Assessing HDR Fidelity
  - 17.3 From Spatial Frequency Errors to Global Quality Measure of HDR Content: Improvement of the HVS-Based Model
  - 17.4 Adapted LDR Metrics for Measuring HDR Image Quality in the Context of Compression
  - 17.5 Tone Mapping and Dynamic Range-Independent Metrics
  - 17.6 Extensions to Video
  - 17.7 Concluding Remarks
Part VI: Applications
- Chapter 18: HDR Imaging in Automotive Applications
  - Abstract
  - Acknowledgments
  - 18.1 History and Motivation for High Dynamic Range Sensors and Cameras
  - 18.2 Requirements for Automotive Camera Sensors
  - 18.3 HDR Implementations
  - 18.4 HDR Video-Based Driver Assistance Applications
- Chapter 19: An Application of HDR in Medical Imaging
  - Abstract
  - Acknowledgments
  - 19.1 Introduction
  - 19.2 Requirements of HDR Visualization in the Medical Field
  - 19.3 Evaluation of Medical HDR Displays
  - 19.4 The Dual-Layer Approach
  - 19.5 Conclusions
- Chapter 20: High Dynamic Range Digital Imaging of Spacecraft
  - Abstract
  - Acknowledgments
  - 20.1 Introduction
  - 20.2 Background
  - 20.3 Film Baseline
  - 20.4 HDR Imaging of Spacecraft Field Experiments
  - 20.5 Calibrated Measurement of Imager Dynamic Range
  - 20.6 HDR Workflow and Display Device Luminance
  - 20.7 Conclusions
- Chapter 21: The Dynamic Range of Driving Simulation
  - Abstract
  - 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
- Chapter 22: HDR Image Watermarking
  - Abstract
  - 22.1 A Brief Introduction to Digital Watermarking
  - 22.2 Digital Watermarking for HDR Images
  - 22.3 Concluding Remarks
Index

Frédéric Dufaux

Frédéric Dufaux is a CNRS Research Director at Telecom ParisTech. He is also Editor-in-Chief of Signal Processing: Image Communication.

Frédéric received his M.Sc. in physics and Ph.D. in electrical engineering from EPFL in 1990 and 1994 respectively. He has over 20 years of experience in research, previously holding positions at EPFL, Emitall Surveillance, Genimedia, Compaq, Digital Equipment, MIT, and Bell Labs. He has been involved in the standardization of digital video and imaging technologies, participating both in the MPEG and JPEG committees. He is the recipient of two ISO awards for his contributions. Frédéric was Vice General Chair of ICIP 2014. He is an elected member of the IEEE Image, Video, and Multidimensional Signal Processing (IVMSP) and Multimedia Signal Processing (MMSP) Technical Committees. He is also the Chair of the EURASIP Special Area Team on Visual Information Processing.

His research interests include image and video coding, distributed video coding, 3D video, high dynamic range imaging, visual quality assessment, video surveillance, privacy protection, image and video analysis, multimedia content search and retrieval, and video transmission over wireless network. He is the author or co-author of more than 120 research publications and holds 17 patents issued or pending.

Affiliations and expertise

Institut Mines-Télécom, Télécom ParisTech, CNRS LTCI, Paris, France

Patrick Le Callet

Patrick Le Callet is Professor at University of Nantes/Polytech Nantes and leading research in IRCCyN/CNRS lab. He received both an M.Sc. and a PhD degree in image processing from Ecole polytechnique de l’Université de Nantes. He was also a student at the Ecole Normale Superieure de Cachan where he sat the “Aggrégation” (credentialing exam) in electronics of the French National Education. He worked as an Assistant Professor from 1997 to 1999 and as a full time lecturer from 1999 to 2003 at the Department of Electrical Engineering of Technical Institute of the University of Nantes (IUT). Since 2003 he teaches at Ecole polytechnique de l’Université de Nantes (Engineering School) in the Electrical Engineering and the Computer Science departments where is now a Full Professor. Since 2006, he is the head of the Image and Video Communication lab at CNRS IRCCyN, a group of more than 35 researchers. He is mostly engaged in research dealing with the application of human vision modeling in image and video processing. His current centers of interest are 3D image and video quality assessment, watermarking techniques and visual attention modeling and applications. He is co-author of more than 200 publications and communications and co-inventor of 13 international patents on these topics. He also co-chairs within the VQEG (Video Quality Expert Group) the “HDR Group” and “3DTV” activities. He is currently serving as associate editor for IEEE transactions on Image Processing, IEEE transactions on Circuit System and Video Technology, SPRINGER EURASIP Journal on Image and Video Processing, and SPIE Electronic Imaging.

Affiliations and expertise

Université de Nantes, France

Rafal Mantiuk

Rafal Mantiuk is a senior lecturer at the Computer Laboratory, University of Cambridge (UK). He received his PhD from the Max-Planck-Institute for Computer Science (2006, Germany), was a postdoctoral researcher at the University of British Columbia (Canada) and a lecturer at Bangor University (UK). He has published numerous journal and conference papers presented at ACM SIGGRAPH, Eurographics, CVPR and SPIE HVEI conferences, has been awarded several patents and was recognized by the Heinz Billing Award (2006). He made contributions to the field of high dynamic range imaging in the areas of video compression, tone-mapping and quality assessment. Rafal Mantiuk investigates how the knowledge of the human visual system and perception can be incorporated within computer graphics and imaging algorithms. His recent interests focus on designing imaging algorithms that adapt to human visual performance and viewing conditions in order to deliver the best images given limited resources, such as bandwidth, computation time or display contrast.

Affiliations and expertise

Senior lecturer, University of Cambridge (UK)

Marta Mrak

Marta Mrak received the Dipl. Ing. and M.Sc. degrees in electronic engineering from the University of Zagreb, Croatia, and the Ph.D. degree from Queen Mary University of London, UK. Before joining Research and Development Department at the BBC in 2010 to work on video compression research and the H.265/HEVC standardization, she was a postdoctoral researcher at the University of Surrey and Queen Mary University of London. In 2002 she was awarded a German DAAD scholarship for video compression research at Heinrich Hertz Institute, Germany. She co-authored more than 100 papers, book chapters and standardization contributions, and co-edited a book on High-Quality Visual Experience (Springer, 2010). She has been involved in several projects funded by European and UK research councils in roles ranging from researcher to scientific coordinator. She is a member of the Multimedia Signal Processing technical committee of the IEEE, senior member of IEEE, area editor of the Elsevier journal Signal Processing: Image Communication and guest editor of several special issues in relevant journals in the field.

Affiliations and expertise

BBC, UK

Life Sciences

Physical Sciences & Engineering

Social Sciences & Humanities

Health

High Dynamic Range Video

From Acquisition, to Display and Applications

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Frédéric Dufaux

Patrick Le Callet

Rafal Mantiuk

Marta Mrak

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