High Dynamic Range Video: Concepts, Technologies and Applications gives an introduction to a full range of topics within the end-to-end HDR video pipeline, covering the issues around capturing HDR and stereo HDR video, such as ghosting and use of legacy LDR systems, how HDR video can be manipulated, including real-time mixing, the very latest designs for HDR displays, HDR video on mobile devices, and the applications of HDR video.
With this book, the reader will gain an overview of the current state-of-the art of HDR video, learn the potential of HDR video to provide a step change to a wide range of imaging applications, and attain the knowledge needed to introduce HDR video in their own applications.
- Written by experts who have been actively researching High Dynamic Range Video
- Covers a full range of topics within the end-to-end HDR video pipeline
- Provides applications that demonstrate how HDR video can be applied
Muu info
Comprehensive source on the key technologies, applications, and latest advancements in High Dynamic Range (HDR) video, including mobile applications
Contributors |
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ix | |
Editors' Biography |
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xi | |
Acknowledgments |
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xiii | |
Overview of HDR Video |
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xv | |
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1 | (108) |
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3 | (42) |
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K. Karaduzovic-Hadziabdic |
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3 | (2) |
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2 Image Acquisition Model |
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5 | (1) |
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3 HDR Image Deghosting Methods |
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6 | (2) |
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4 HDR Video Capture Methods |
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8 | (6) |
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5 Global Video Deghosting |
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14 | (6) |
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20 | (25) |
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38 | (7) |
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2 Creating HDR Video Using Retargeting |
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45 | (16) |
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45 | (1) |
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2 Background in HDR Video and Image Retargeting |
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46 | (4) |
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3 Dynamic Camera and Static Scene |
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50 | (3) |
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4 Static Camera and Dynamic Scene |
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53 | (4) |
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57 | (4) |
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58 | (3) |
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3 HDR Multiview Image Sequence Generation: Toward 3D HDR Video |
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61 | (26) |
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61 | (4) |
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2 Multiple Exposure Stereo Matching |
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65 | (6) |
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3 Patch-Based Multiscopic HDR Generation |
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71 | (6) |
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77 | (10) |
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84 | (3) |
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4 Calibrated Measurement of Imager Dynamic Range |
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87 | (22) |
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87 | (7) |
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94 | (8) |
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102 | (2) |
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104 | (2) |
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106 | (3) |
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106 | (1) |
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107 | (2) |
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109 | (62) |
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111 | (18) |
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111 | (1) |
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2 Image and Video Quality Assessment |
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111 | (3) |
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114 | (6) |
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120 | (3) |
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123 | (1) |
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6 Outlook and Future Work |
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124 | (5) |
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124 | (1) |
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125 | (4) |
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6 Practical Backwards Compatible High Dynamic Range Compression |
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129 | (16) |
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129 | (1) |
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130 | (3) |
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3 Practical Backwards Compatible Compression |
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133 | (3) |
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136 | (6) |
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142 | (3) |
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142 | (1) |
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143 | (2) |
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7 Real-Time HDR Video Processing and Compression Using an FPGA |
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145 | (10) |
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145 | (1) |
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2 Description of the HDR Acquisition and Compression Task |
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146 | (1) |
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3 Acquisition of HDR Video |
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147 | (2) |
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4 HDR Video Compression Implementation |
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149 | (2) |
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5 HDR Acquisition and Compression System Interfaces |
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151 | (1) |
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6 HDR Acquisition and Compression Software Structure Overview |
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152 | (1) |
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7 HDR Acquisition and Compressions Features and Results |
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152 | (3) |
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153 | (2) |
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8 Live HDR Video Broadcast Production |
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155 | (16) |
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155 | (4) |
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159 | (5) |
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3 Integration of HDR Flows in Standard Broadcasting Pipelines |
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164 | (1) |
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4 GPU-Based Real-Time Manipulation and Monitoring |
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165 | (3) |
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168 | (3) |
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169 | (2) |
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171 | (30) |
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9 HDR Video on Small Screen Devices |
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173 | (16) |
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173 | (1) |
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174 | (15) |
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187 | (1) |
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187 | (2) |
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10 Gaze-Dependent Tone Mapping for HDR Video |
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189 | (12) |
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189 | (1) |
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190 | (2) |
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3 Gaze-Dependent Tone Compression |
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192 | (4) |
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196 | (2) |
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5 Conclusions and Future Work |
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198 | (3) |
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198 | (1) |
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198 | (3) |
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Part 4 Applications and Uptake |
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201 | (42) |
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11 Improving Tracking Accuracy Using Illumination Neutralization and High Dynamic Range Imaging |
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203 | (12) |
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203 | (1) |
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204 | (1) |
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3 Acquisition of the Scene Illumination |
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205 | (3) |
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4 Precomputed Radiance Transfer |
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208 | (1) |
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5 Neutralizing Illumination |
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209 | (1) |
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6 Improving Tracking Accuracy |
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210 | (2) |
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212 | (3) |
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212 | (3) |
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12 Factors Influencing the Widespread Uptake of HDR Video |
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215 | (28) |
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215 | (5) |
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2 Current HDR Video Television Adoption: What and Why |
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220 | (6) |
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3 Current Adoption: Short Term or Enduring? |
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226 | (4) |
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4 Supply Conditions and HDR Adoption |
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230 | (4) |
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5 Coordination and the Role of Technology Standards |
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234 | (4) |
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238 | (5) |
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239 | (4) |
Index |
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243 | |
Alan Chalmers is Professor of Visualisation and Royal Society Industrial Fellow at University of Warwick and co-founder of the spinout company TrueDR Ltd. Previously he was a founder and CEO of the spinout company goHDR Ltd. He has published over 230 papers in journals and international conferences on high-fidelity virtual environments and HDR imaging and successfully supervised 37 PhD students. He is Honorary President of Afrigraph, a Fellow of the ERA Foundation, and formerly Vice President of ACM SIGGRAPH. Together with SpheronVR, he was instrumental in the development of the worlds first HDR video camera, which was completed in July 2009. From 2011-2015 he was Chair of the EU COST Action IC1005 HDRi: The digital capture, storage, transmission and display of real-world lighting” [ ic1005]. This co-ordinated research and development in HDR across 25 EU countries and 44 institutions. In addition, Chalmers is a UK representative on IST/37 considering HDR standards within MPEG. Patrizio Campisi received the Ph.D. degree in Electrical Engineering from Roma Tre University, Rome, Italy, where he is Full Professor at the Section of Applied Electronics, Dept. of Engineering. His research interests are in the area of secure multimedia communications and biometrics. Specifically, he has been working on secure biometric recognition, digital watermarking, image deconvolution, image analysis, stereo image and video processing, blind equalization of data signals, and secure communications. He has been the General Chair of the seventh IEEE Workshop on Information Forensics and Security”, WIFS 2015, November 2015, Rome, Italy, and of the 12th ACM Workshop on Multimedia and Security, September 2010, Italy. He has been technical co-Chair of the 1st ACM Workshop on Information Hiding and Multimedia Security, June 2013,France and of the ”Fourth IEEE Workshop on Information Forensics and Security”, WIFS 2012, December 2012, Spain. He is the editor of the book ”Security and Privacy in Biometrics”, SPRINGER, July 2013. He is co-editor of the book ”Blind Image Deconvolution: theory and applications”, CRC press, May 2007. He is co-recipient of an IEEE ICIP06 and IEEE BTAS 2008 best student paper award and of an IEEE Biometric Symposium 2007 best paper award. He has been Associate editor of IEEE Signal Processing Letters and of IEEE Transactions on Information Forensics and Security. He is currently Senior Associate editor of IEEE Signal Processing Letters. He is IEEE SPS Director Student Services. He is a member of the IEEE Technical Committee on Information Assurance & Intelligent Multimedia-Mobile Communications, System, Man, and Cybernetics Society and was a member of the IEEE Certified Biometric Program (CBP) Learning System Committee. Peter Shirley is a Distinguished Research Scientist at NVIDIA. He was formally a co-founder two software companies and a professor at various universities. He received a BS in Physics from Reed College in 1985 and a Ph.D. in Computer Science from University of Illinois in 1991. He is the coauthor of several books on computer graphics and a variety of technical articles. His professional interests include interactive and HDR imaging, computational photography, realistic rendering, statistical computing, visualization, and immersive environments. Dr. Igor García Olaizola obtained his degree in Electronics Engineering by the Universidad of Navarra (Tecnun) in (2001). In 2001 he worked as research assistant in Fraunhofer Institut für Integrierte Schaltungen (IIS), Erlangen (Germany) were he worked in the development of MPEG audio decoders (MP3 & AAC) on FPGAs and DSPs. In 2002 he started as part of the research team of Vicomtech. In 2006 he worked for Vilau (a media engineering company) in consulting, depevelopment and deployment activities especially in the Digital TV market. Since 2007, Igor is the head of Digital Media department in Vicomtech where he has actively participated in R&D projects related with Media Production and Broadcasting technologies. In 2013 he received his PhD in Computer Science and Artificial Intelligence by the Faculty of Computer Science of the University of the Basque Country. Igor participated in the COST Action IC1005 HDRi as dissemination chair and currently is associated lecturer in Tecnun. His main research interests are related with multimedia processing and analysis techniques with a special focus on broadcasting technologies.