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Contents
Foreword
Preface
1 Introduction
1.1 Light, Human Vision, and Color Spaces
2 HDR Pipeline
2.1 Acquisition of HDR Content
2.2 HDR Content Storing
2.3 Native Visualization
3 Tone Mapping
3.1 TMO Matlabr® Framework
3.2 Global Operators
3.3 Local Operators
3.4 Frequency-Based/Gradient Domain Operators
3.5 Segmentation Operators
3.6 Summary
4 New Trends in Tone Mapping
4.1 A general Approach to Tone Mapping
4.2 Color Management in Tone Mapping
4.3 Summary
5 HDR Video Tone Mapping
5.1 Temporal Artifacts
5.2 HDR Videos MATLAB Framework
5.3 Global Temporal Methods
5.4 Temporal Local Methods
5.5 Real-Time HDR Video Tone Mapping
5.6 Summary
6 Expansion Operators for Low Dynamic Range Content
6.1 EO MATLAB Framework
6.2 Linearization of the Signal Using a Single Image
6.3 Decontouring Models for High Contrast Displays
6.4 Global Models
6.5 Classification Models
6.6 Expand Map Models
6.7 User-Based Models: HDR Hallucination
6.8 Summary
7 Image-Based Lighting
7.1 Environment Maps
7.2 Rendering with IBL
7.3 Summary
8 HDR Images Compression
8.1 HDR Compression MATLAB Framework
8.2 HDR Image Compression
8.3 HDR Texture Compression
8.4 Summary
9 HDR Video Compression
9.1 Perception-Motivated High Dynamic Range Video Encoding
9.2 Backward Compatible HDR-MPEG
9.3 Rate-Distortion Optimized Compression
9.4 Temporally Coherent Luminance-to-Luma Mapping
9.5 Optimizing a Tone Mapping Curve for Encoding
9.6 Perceptual Quantizer
9.7 Hybrid Log Gamma
9.8 Others Methods
9.9 Summary
10 Evaluation
10.1 Metrics
10.2 Experimental Evaluation Overview
10.3 Experimental Evaluation of Tone Mapping
10.4 Experimental Evaluation of Expansion Operators
10.5 HDR Compression Evaluation
10.6 Summary
A The Bilateral Filter
B Practical Color Spaces
C A Brief Overview of the MATLAB HDR Toolbox
Bibliography
Index
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Foreword
High dynamic range (HDR) imaging has become an essential topic across all of the imaging disciplines – including photography, computer graphics, image processing, and computer vision. HDR is used in diverse applications including the creation of fine art, and the collection of data for scientific analysis. The first edition of Advanced High Dynamic Range Imaging presented a complete treatment of the subject ranging from the acquisition of HDR to be used as data for lighting computer graphics scenes to the processing of HDR for display on a wide selection of devices. The first edition covered the theory of HDR, and also provided practical MATLAB® code for the reader to use. I used the first edition both in a computer graphics course on “Photography-Based Computer Graphics” and in various student research pro jects for acquiring light scattering properties of materials.
Over the past 5 years, not only has the usage of HDR increased, but also research in HDR has continued and accelerated. This second edition of the book covers the important recent advances. There are key updates on many of the topics that were already active at the time of the first edition – acquisition, color management, tone mapping, adapting low dynamic range content to HDR displays, and metrics. In these areas, many initial techniques have been replaced by sophisticated and mature approaches.
The most significant recent advance included in this edition, however, is the emergence of high dynamic range video as a practical medium. High dynamic range video required substantial research rather than simply applying previous work for still images to multiple images. For acquisition, affordable hardware that could rapidly take multiple exposures was needed, and effective de-ghosting algorithms were needed to combine the exposures of changing scenes. Tone mapping and color management for video requires temporal consistency, and investigation of new types of potential perceptual artifacts. The sheer quantity of data for video demands more effective compression schemes.
This new edition is a timely update and expansion of the original text. Practitioners, educat...
