High Dynamic Range Imaging: Acquisition, Display, and Image-Based Lighting

Erik Reinhard, Greg Ward, Sumanta Pattanaik, Paul Debevec




High dynamic range imaging produces images with a much greater range of light and color than conventional imaging. The effect is stunning, as great as the difference between black-and-white and color television. High Dynamic Range Imaging is the first book to describe this exciting new field that is transforming the media and entertainment industries. Written by the foremost researchers in HDRI, it will explain and define this new technology for anyone who works with images, whether it is for computer graphics, film, video, photography, or lighting design.


Table of Contents


1 Introduction

2 Light And Color
2.1 Radiometry
2.2 Photometry
2.3 Colorimetry
2.4 Color Spaces
2.5 White Point and Illuminants
2.6 Color Correction
2.7 Color Opponent Spaces
2.8 Color Appearance
2.9 Display Gamma
2.10 Brightness Encoding
2.11 Standard RGB Color Spaces

3 HDR Image Encodings
3.1 LDR versus HDR Encodings
3.2 Applications of HDR Images
3.3 HDR Image Formats
3.4 HDR Encoding Comparison
3.5 Conclusions

4 HDR Image Capture
4.1 Photography and Light Measurement
4.2 HDR Image Capture from Multiple Exposures
4.3 Film Scanning
4.4 Image Registration and Alignment
4.5 The Mean Threshold Bitmap Alignment Technique
4.6 Deriving the Camera Response Function
4.7 Ghost Removal
4.8 Lens Flare Removal
4.9 Direct Capture of HDR Imagery
4.10 Conclusions

5 Display Devices
5.1 Hardcopy Devices
5.2 Softcopy Devices

6 The Human Visual System and HDR Tone Mapping
6.1 Tone-mapping Problem
6.2 Human Visual Adaptation
6.3 Visual Adaptation Models for HDR Tone Mapping
6.4 Background Intensity in Complex Images
6.5 Dynamics of Visual Adaptation
6.6 Summary

7 Spatial Tone Reproduction
7.1 Preliminaries
7.2 Global Operators
7.3 Local Operators
7.4 Summary

8 Frequency Domain And Gradient Domain Tone Reproduction
8.1 Frequency Domain Operators
8.2 Gradient Domain Operators
8.3 Performance
8.4 Discussion

9 Image-Based Lighting
9.1 Introduction
9.2 Basic Image-based Lighting
9.3 Capturing Light Probe Images
9.4 Omnidirectional Image Mappings
9.5 How a Global Illumination Renderer Computes IBL Images
9.6 Sampling Incident Illumination Efficiently
9.7 Simulating Shadows and Scene-Object Interreflection
9.8 Useful IBL Approximations
9.9 Image-based Lighting for Real Objects and People
9.10 Conclusions

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