High Dynamic Range Video

As new displays and cameras offer enhanced color capabilities, there is a need to extend the precision of digital content. High Dynamic Range (HDR) imaging encodes images and video with higher than normal 8 bit-per-color-channel precision, enabling representation of the complete color gamut and the full visible range of luminance.However, to realize transition from the traditional toHDRimaging, it is necessary to develop imaging algorithms that work with the high-precision data. Tomake such algorithms effective and feasible in practice, it is necessary to take advantage of the limitations of the human visual system by aligning the data shortcomings to those of the human eye, thus limiting storage and processing precision. Therefore, human visual perception is the key component of the solutions we discuss in this book. This book presents a complete pipeline forHDR image and video processing fromacquisition, through compression and quality evaluation, to display. At the HDR image and video acquisition stage specialized HDR sensors or multi-exposure techniques suitable for traditional cameras are discussed. Then, we present a practical solution for pixel values calibration in terms of photometric or radiometric quantities, which are required in some technically oriented applications. Also, we cover the problem of efficient image and video compression and encoding either for storage or transmission purposes, including the aspect of backward compatibility with existing formats. Finally, we review existing HDR display technologies and the associated problems of image contrast and brightness adjustment. For this purpose tone mapping is employed to accommodate HDR content to LDR devices. Conversely, the so-called inverse tone mapping is required to upgrade LDR content for displaying on HDR devices. We overview HDR-enabled image and video quality metrics, which are needed toverify algorithms at all stages of the pipeline. Additionally, we cover successful examples of the HDR technology applications, in particular, in computer graphics and computer vision. The goal of this book is to present all discussed components of the HDR pipeline with the main focus on video. For some pipeline stages HDR video solutions are either not well established or do not exist at all, in which case we describe techniques for single HDR images. In such cases we attempt to select the techniques, which can be extended into temporal domain. Whenever needed, relevant background information on human perception is given, which enables better understanding of the design choices behind the discussed algorithms and HDR equipment. Table of Contents: Introduction / Representation of an HDR Image / HDR Image and Video Acquisition / HDR Image Quality / HDR Image, Video, and Texture Compression / Tone Reproduction / HDR Display Devices / LDR2HDR: Recovering Dynamic Range in Legacy Content / HDRI in Computer Graphics / Software

Auteur

Karol Myszkowski is a senior researcher in the Computer Graphics Group of Max-Planck[1]Institut fur Informatik. From 1993 to 2000 he served as a tenured Associate Professor at the University of Aizu, Japan, and from 1985 to 1993 he worked as a Research Associate and then an Assistant Professor at the Szczecin University of Technology, Poland. In the period 1986-1992 he collaborated with Japanese company Integra, Inc. developing rendering software for such customers as Toshiba Lighting, Shiseido, Matsushita Electric, Kandenko, and others. He received his MSc degree in control engineering from the Szczecin University of Technology in 1983, and his PhD and habilitation degrees in computer science from Warsaw University of Technology (Poland) in 1991 and 2001, respectively. His research interests include perception issues in graphics, high-dynamic range imaging, global illumination, rendering and animation. Myszkowski has written over 80 refereed publications on these subjects and has served on numerous program committees. He was the Program Committee co-chair of Eurographics Rendering Symposium in 2001, ACM Applied Perception in Graphics and Visualization in 2008, and Spring School of Computer Graphics in 2008. Myszkowski has supervised over 30 graduate and undergraduate research projects. Rafal Mantiuk (PhD from the Max-Planck-Institut for Computer Science, Germany; Msc in Computer Science from the Szczecin University of Technology, Poland) is postdoctoral fellow at the University of British Columbia, Canada. He combines in his research the aspects of human perception, color appearance, image processing, and computer graphics to address the problems of future imaging systems, in which the human eye rather than technology is the major limiting factor. During the last five years he has been involved in research at Max-Planck[1]Institut for Computer Science, Sharp Laboratories of America, and BrightSide Technologies (Dolby Canada). Rafal authored several patents and papers on high-dynamic range (HDR) image and video compression (Proc. of SIGGRAPH'04 and '06), tone-mapping (ACM TAP, EG'06), developed a fidelity metric for HDR images (HDR-VDP) and co-maintains popular software for HDR processing-pfstools. In 2006 he was granted the Heinz Billing Award for his work. Grzegorz Krawczyk received PhD from the Max-Planck-Institut for Computer Science, Germany and MSc in Computer Science from the Szczecin University of Technology, Poland. During the last five years he has been involved in the research projects in collaboration with the book HDR VIDEO University of British Columbia and BrightSide Technologies (Dolby Canada). His research focuses on the insightful application of knowledge about human visual system to assure high fidelity in high dynamic range (HDR) images and video. Grzegorz authored several papers on HDR tone mapping (Eurographics '05, '06, and '07) and HDR video compression (ACM Siggraph '04). He also co-maintains a popular software for HDR processing, capture and tone mapping-pfstools, pfscalibration and pfstmo.

Contenu
Introduction.- Representation of an HDR Image.- HDR Image and Video Acquisition.- HDR Image Quality.- HDR Image, Video, and Texture Compression.- Tone Reproduction.- HDR Display Devices.- LDR2HDR: Recovering Dynamic Range in Legacy Content.- HDRI in Computer Graphics.- Software.