High Dynamic Range Hdr Vision

This first comprehensive account of high-dynamic-range (HDR) vision focuses on HDR real-time, high-speed digital video recording and also systematically presents HDR video transmission and display. While the book conveys the overall picture of HDR vision, specific knowledge of microelectronics and image processing is not required. In this book, experts share their knowledge in this rapidly evolving art related to the single most powerful of our senses.

At the time of rapid technological progress and uptake of High Dynamic Range (HDR) video content in numerous sectors, this book provides an overview of the key supporting technologies, discusses the effectiveness of various techniques, reviews the initial standardization efforts and explores new research directions in all aspects involved in HDR video systems. Topics addressed include content acquisition and production, tone mapping and inverse tone mapping operators, coding, quality of experience, and display technologies. This book also explores a number of applications using HDR video technologies in the automotive industry, medical imaging, spacecraft imaging, driving simulation and watermarking. By covering general to advanced topics, along with a broad and deep analysis, this book is suitable for both the researcher new or familiar to the area. With this book the reader will: Gain a broad understanding of all the elements in the HDR video processing chain Learn the most recent results of ongoing research Understand the challenges and perspectives for HDR video technologies Covers a broad range of topics encompassing the whole processing chain in HDR video systems, from acquisition to display Provides a comprehensive overview of this fast emerging topic Presents upcoming applications taking advantages of HDR

Techniques for high dynamic range (HDR) imaging make it possible to capture and store an increased range of luminances and colors as compared to what can be achieved with a conventional camera. This high amount of image information can be used in a wide range of applications, such as HDR displays, image-based lighting, tone-mapping, computer vision, and post-processing operations. HDR imaging has been an important concept in research and development for many years. Within the last couple of years it has also reached the consumer market, e.g. with TV displays that are capable of reproducing an increased dynamic range and peak luminance. This thesis presents a set of technical contributions within the field of HDR imaging. First, the area of HDR video tone-mapping is thoroughly reviewed, evaluated and developed upon. A subjective comparison experiment of existing methods is performed, followed by the development of novel techniques that overcome many of the problems evidenced by the evaluation. Second, a largescale objective comparison is presented, which evaluates existing techniques that are involved in HDR video distribution. From the results, a first open-source HDR video codec solution, Luma HDRv, is built using the best performing techniques. Third, a machine learning method is proposed for the purpose of reconstructing an HDR image from one single-exposure low dynamic range (LDR) image. The method is trained on a large set of HDR images, using recent advances in deep learning, and the results increase the quality and performance significantly as compared to existing algorithms. The areas for which contributions are presented can be closely inter-linked in the HDR imaging pipeline. Here, the thesis work helps in promoting efficient and high-quality HDR video distribution and display, as well as robust HDR image reconstruction from a single conventional LDR image.

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

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 to verify 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

This book explores the methods needed for creating and manipulating HDR content. HDR is a step change from traditional imaging; more closely matching what we see with our eyes. In the years since the first edition of this book appeared, HDR has become much more widespread, moving from a research concept to a standard imaging method. This new edition incorporates all the many developments in HDR since the first edition and once again emphasizes practical tips, including the authors' popular HDR Toolbox (available on the authors' website) for MATLAB and gives readers the tools they need to develop and experiment with new techniques for creating compelling HDR content. Key Features: Contains the HDR Toolbox for readers' experimentation on authors' website Offers an up-to-date, detailed guide to the theory and practice of high dynamic range imaging Covers all aspects of the field, from capture to display Provides benchmarks for evaluating HDR imagery

Rendering High Dynamic Range (HDR) scenes on media with limited dynamic range began in the Renaissance whereby painters, then photographers, learned to use low-range spatial techniques to synthesize appearances, rather than to reproduce accurately the light from scenes. The Art and Science of HDR Imaging presents a unique scientific HDR approach derived from artists’ understanding of painting, emphasizing spatial information in electronic imaging. Human visual appearance and reproduction rendition of the HDR world requires spatial-image processing to overcome the veiling glare limits of optical imaging, in eyes and in cameras. Illustrated in full colour throughout, including examples of fine-art paintings, HDR photography, and multiple exposure scenes; this book uses techniques to study the HDR properties of entire scenes, and measures the range of light of scenes and the range that cameras capture. It describes how electronic image processing has been used to render HDR scenes since 1967, and examines the great variety of HDR algorithms used today. Showing how spatial processes can mimic vision, and render scenes as artists do, the book also: Gives the history of HDR from artists' spatial techniques to scientific image processing Measures and describes the limits of HDR scenes, HDR camera images, and the range of HDR appearances Offers a unique review of the entire family of Retinex image processing algorithms Describes the considerable overlap of HDR and Color Constancy: two sides of the same coin Explains the advantages of algorithms that replicate human vision in the processing of HDR scenes Provides extensive data to test algorithms and models of vision on an accompanying website www.wiley.com/go/mccannhdr

To enhance the overall viewing experience (for cinema, TV, games, AR/VR) the media industry is continuously striving to improve image quality. Currently the emphasis is on High Dynamic Range (HDR) and Wide Colour Gamut (WCG) technologies, which yield images with greater contrast and more vivid colours. The uptake of these technologies, however, has been hampered by the significant challenge of understanding the science behind visual perception. Vision Models for High Dynamic Range and Wide Colour Gamut Imaging provides university researchers and graduate students in computer science, computer engineering, vision science, as well as industry R&D engineers, an insight into the science and methods for HDR and WCG. It presents the underlying principles and latest practical methods in a detailed and accessible way, highlighting how the use of vision models is a key element of all state-of-the-art methods for these emerging technologies. Presents the underlying vision science principles and models that are essential to the emerging technologies of HDR and WCG Explores state-of-the-art techniques for tone and gamut mapping Discusses open challenges and future directions of HDR and WCG research