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High Dynamic Range Imaging, Second Edition, is an essential resource for anyone working with images, whether it is for computer graphics, film, video, photography, or lighting design. It describes HDRI technology in its entirety and covers a wide-range of topics, from capture devices to tone reproduction and image-based lighting. The techniques described enable students to produce images that have a dynamic range much closer to that found in the real world, leading to an unparalleled visual experience. This revised edition includes new chapters on High Dynamic Range Video Encoding, High Dynamic Range Image Encoding, and High Dynamic Range Display Devices. All existing chapters have been updated to reflect the current state-of-the-art technology. As both an introduction to the field and an authoritative technical reference, this book is essential for anyone working with images, whether in computer graphics, film, video, photography, or lighting design.
- New material includes chapters on High Dynamic Range Video Encoding, High Dynamic Range Image Encoding, and High Dynammic Range Display Devices
- Written by the inventors and initial implementors of High Dynamic Range Imaging
- Covers the basic concepts (including just enough about human vision to explain why HDR images are necessary), image capture, image encoding, file formats, display techniques, tone mapping for lower dynamic range display, and the use of HDR images and calculations in 3D rendering
- Range and depth of coverage is good for the knowledgeable researcher as well as those who are just starting to learn about High Dynamic Range imaging
The prior edition of this book included a DVD-ROM. Files from the DVD-ROM can be accessed at: http://www.erikreinhard.com/hdr_2nd/index.html
R&D Professionals in computer graphics, digital design and visualization. Visual effects artists in entertainment industry (including interactive entertainment/games). Engineering staff (i.e. coders, implementors of HDRI) at HDRI display/sensor manufacturers (e.g., Phillips, Samsung).
2 Light and Color
2.4 Color Spaces
2.5 White Point and Illuminants
2.6 Spectral Sharpening
2.7 Color Opponent Spaces
2.8 Color Correction
2.9 Color Appearance
2.10 Display Gamma
2.11 Brightness Encoding
2.12 Standard RGB Color Spaces
3 High Dynamic Range Image Encodings
3.1 LDR vs. HDR Encodings
3.2 Applications of HDR Images
3.3 HDR Image Formats
3.4 HDR Encoding Comparison
4 HDR Video Encodings
4.1 Custom HDR Video Coding
4.2 Backward Compatible HDR Video Compression
5 HDR Image Capture
5.1 Photography & Light Measurement
5.2 HDR Image Capture from Multiple Exposures
5.3 Film Scanning
5.4 Image Registration/Alignment
5.5 The Median Threshold Bitmap Alignment Technique
5.6 Other Alignment Methods
5.7 Deriving the Camera Response Function
5.8 Noise Removal
5.9 Ghost Removal
5.10 Lens Flare Removal
5.11 HDR Capture Hardware
6 Display Devices and Printing Technologies
6.1 Display Technologies
6.2 Local Dimming HDR Displays
7 Perception-Based Tone Reproduction
7.1 Tone Mapping Problem
7.2 Human Visual Adaptation
7.3 Visual Adaptation Models for HDR Tone Mapping
7.4 Background Intensity in Complex Images
7.5 Dynamics of Visual Adaptation
7.6 Design Considerations
8 Tone Reproduction Operators
8.1 Sigmoidal Tone Reproduction Operators
8.2 Image AppearanceModels
8.3 Other HVS-Based Models
8.4 Apparent Contrast and Brightness Enhancement
8.5 Other Tone Reproduction Operators
8.6 Exposure Fusion
9 Inverse Tone Reproduction
9.1 Expansion Functions
9.2 Under- and Over-Exposed Material
9.3 Suppressing Quantization and Encoding Artifacts
9.4 A Preference Studies
9.5 Suggested Applications
10 Visible Difference Predictors
10.1 Subjective versus Objective Quality Metrics
10.2 Classification of Objective Quality Metrics
10.3 Full-reference Quality Metrics
10.4 Pixel-based Metrics
10.5 Structural SIMilarity (SSIM) Index
10.6 Perception-based Fidelity Metrics
10.7 The HDR Visible Differences Predictor
10.8 Dynamic Range Independent (DRI) Image Quality Metric
10.9 Supra-Threshold HDR Image Quality Metrics
10.10Accounting for Partial Adaptation
11 Image-Based Lighting
11.2 How the Renderer Computes IBL Images
11.3 Capturing and Representing Light Probe Images
11.4 Omnidirectional Image Mappings
11.5 Capturing very bright sources such as the sun
11.6 The Sampling Problem
11.7 Advanced Image-Based Lighting Techniques
11.8 Useful IBL Approximations
11.9 Image-Based Lighting Real Objects and People
11.10Real-time Image-Based Lighting
A List of Symbols
- No. of pages:
- © Morgan Kaufmann 2010
- 25th May 2010
- Morgan Kaufmann
- Hardcover ISBN:
- eBook ISBN:
Erik Reinhard is assistant professor at the University of Bristol and founder and editor-in-chief (with Heinrich Bülthoff) of ACM Transactions on Applied Perception. He is interested in the interface between visual perception and computer graphics and also in high dynamic range image editing. His work in HDRI includes the SIGGRAPH 2005 Computer Animation Festival contribution Image-based Material Editing, as well as tone reproduction and color appearance algorithms. He holds a BSc and a TWAIO diploma in computer science from Delft University of Technology and a PhD in computer science from the University of Bristol, and was a post-doctoral researcher at the University of Utah.
University of Bristol, UK
Wolfgang Heidrich is Associate Professor and Dolby Research Chair at the Department of Computer Science, University of British Columbia.
Paul Debevec is a research assistant professor at the University of Southern California and the executive producer of graphics research at USC's Institute for Creative Technologies. Paul's PhD thesis (UC Berkeley, 1996) presented Façade, an image-based modeling and rendering system for creating photoreal architectural models from photographs. Using Façade, he led the creation of virtual cinematography of the Berkeley campus for his 1997 film The Campanile Movie whose techniques were used to create virtual backgrounds in the 1999 film The Matrix. Subsequently he pioneered techniques for illuminating computer-generated scenes with real-world lighting captured through high dynamic range photography, demonstrating new image-based lighting techniques in his films Rendering with Natural Light (1998), Fiat Lux (1999), and The Parthenon (2004). He has also led the design of HDR Shop, the first widely used high dynamic range image editing program. Most recently Paul has led the development of a series of Light Stage devices that allow objects, actors, and performances to be synthetically illuminated with novel lighting. This technique was used to create photoreal digital actors for the film Spider Man 2. Paul received the first ACM SIGGRAPH Significant New Researcher Award in 2001, was named one of the world's top "100 Young Innovators" by MIT's Technology Review in 2002, and was awarded a Lillian Gilbreth Lectureship from the National Academy of Engineering in 2005.
Institute for Creative Technologies, University of Southern California, U.S.A.
Sumanta Pattanaik is an associate processor of computer science at the University of Central Florida, Orlando (UCF). His main area of research is realistic rendering where he has been active for over 15 years and has contributed significantly through a number of research publications. His current focus is developing real-time rendering algorithms and modeling natural environments. He is currently serving as the computer graphics category editor of ACM Computing Review. Sumanta received his MS degree in chemistry from Utkal University, India in 1978 and PhD degree in computer science from Birla Institute of Technology and Science in Pilani (BITS-Pilani), India in 1993. Prior to joining UCF he was a research associate at the Program of Computer Graphics at Cornell University, a post-doctoral researcher at the SIAMES program of IRISA/INRIA France, and a senior staff scientist at the National Center of Software Technology, India.
University of Central Florida, Orlando, U.S.A.
Greg Ward is a pioneer in HDRI, having developed the first widely used HDR image file format in 1986 as part of the Radiance lighting simulation system. In 1998 he introduced the more advanced LogLuv TIFF encoding and more recently the backwards-compatible HDR extension to JPEG. He is also the author of the Mac OS X application Photosphere, which provides advanced HDR assembly and cataloging and is freely available from www.anyhere.com. Currently he is collaborating with Sunnybrook Technologies on their HDR display systems. Greg has worked as a part of the computer graphics research community for over 20 years, developing rendering algorithms, reflectance models and measurement systems, tone reproduction operators, image processing techniques, and photo printer calibration methods. His past employers include the Lawrence Berkeley National Laboratory, EPFL Switzerland, SGI, Shutterfly, and Exponent. He holds a bachelor's degree in physics from UC Berkeley and a master's degree in computer science from San Francisco State University. He is currently working as an independent consultant in Albany, California.
Independent Consultant, Albany, California, U.S.A.
Karol Myszkowski is a Senior Researcher in the Computer Graphics Group of
the Max-Planck-Institut für Informatik (Germany).
Senior Researcher in the Computer Graphics Group of the Max-Planck-Institut für Informatik (Germany).
"With the mainstream introduction of affordable LED HDTVs and computer monitors, the principles of high dynamic range imaging have gone from an academic research topic to essential knowledge. For anyone involved in software or hardware development for computer games and entertainment video, this second edition of High Dynamic Range Imaging offers everything you need and more. Highly recommended." --Ian Ashdown, President, byHeart Consultants Limited
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