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High dynamic range imaging

Published: 08 August 2004 Publication History

Abstract

Current display devices can display only a limited range of contrast and colors, which is one of the main reasons that most image acquisition, processing, and display techniques use no more than eight bits per color channel. This course outlines recent advances in high-dynamic-range imaging, from capture to display, that remove this restriction, thereby enabling images to represent the color gamut and dynamic range of the original scene rather than the limited subspace imposed by current monitor technology. This hands-on course teaches how high-dynamic-range images can be captured, the file formats available to store them, and the algorithms required to prepare them for display on low-dynamic-range display devices. The trade-offs at each stage, from capture to display, are assessed, allowing attendees to make informed choices about data-capture techniques, file formats, and tone-reproduction operators. The course also covers recent advances in image-based lighting, in which HDR images can be used to illuminate CG objects and realistically integrate them into real-world scenes. Through practical examples taken from photography and the film industry, it shows the vast improvements in image fidelity afforded by high-dynamic-range imaging.

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  • (2024)Multi-Exposed Image Fusion using Multiscale-Surround Switching MapThe Journal of Korean Institute of Information Technology10.14801/jkiit.2024.22.5.13922:5(139-150)Online publication date: 31-May-2024
  • (2024)Towards Co-Evaluation of Cameras, HDR, and Algorithms for Industrial-Grade 6DoF Pose Estimation2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR52733.2024.02141(22691-22701)Online publication date: 16-Jun-2024
  • (2024)Multi exposure fusion for high dynamic range imaging via multi-channel gradient tensorDigital Signal Processing10.1016/j.dsp.2024.104821(104821)Online publication date: Oct-2024
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cover image ACM Conferences
SIGGRAPH '04: ACM SIGGRAPH 2004 Course Notes
August 2004
6109 pages
ISBN:9781450378017
DOI:10.1145/1103900
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 August 2004

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Cited By

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  • (2024)Multi-Exposed Image Fusion using Multiscale-Surround Switching MapThe Journal of Korean Institute of Information Technology10.14801/jkiit.2024.22.5.13922:5(139-150)Online publication date: 31-May-2024
  • (2024)Towards Co-Evaluation of Cameras, HDR, and Algorithms for Industrial-Grade 6DoF Pose Estimation2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)10.1109/CVPR52733.2024.02141(22691-22701)Online publication date: 16-Jun-2024
  • (2024)Multi exposure fusion for high dynamic range imaging via multi-channel gradient tensorDigital Signal Processing10.1016/j.dsp.2024.104821(104821)Online publication date: Oct-2024
  • (2021)Research on Dynamic Range Analysis and Improvement of Imaging Equipment2021 Workshop on Algorithm and Big Data10.1145/3456389.3456392(40-44)Online publication date: 12-Mar-2021
  • (2019)A New Calibration Process for a Homogeneous Cyclorama Illumination in Virtual TV SetsApplied Sciences10.3390/app91020209:10(2020)Online publication date: 16-May-2019
  • (2019)Detail-Preserving Exposure Fusion Based on Adaptive Structure Patch Decomposition2019 IEEE International Conference on Signal Processing, Communications and Computing (ICSPCC)10.1109/ICSPCC46631.2019.8960859(1-5)Online publication date: Sep-2019
  • (2017)Blind IQA for Pictures in extreme conditions: Experimental evaluation on metallic surfaces2017 Latin American Robotics Symposium (LARS) and 2017 Brazilian Symposium on Robotics (SBR)10.1109/SBR-LARS-R.2017.8215341(1-6)Online publication date: Nov-2017
  • (2017)Adaptive Quantization-Based HDR Video Coding with HEVC Main 10 Profile2017 IEEE International Symposium on Multimedia (ISM)10.1109/ISM.2017.65(350-353)Online publication date: Dec-2017
  • (2014)A Novel Detail-Enhanced Exposure Fusion Method Based on Local FeatureIntelligent Computing Theory10.1007/978-3-319-09333-8_44(407-414)Online publication date: 2014
  • (2013)Convolution engineACM SIGARCH Computer Architecture News10.1145/2508148.248592541:3(24-35)Online publication date: 23-Jun-2013
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