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High Dynamic Range Imaging Pipeline: Perception-Motivated Representation of Visual Content

MPG-Autoren

Mantiuk,  Rafał
Max Planck Society;

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Krawczyk,  Grzegorz
Computer Graphics, MPI for Informatics, Max Planck Society;

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Mantiuk,  Radoslaw
Computer Graphics, MPI for Informatics, Max Planck Society;

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Seidel,  Hans-Peter       
Computer Graphics, MPI for Informatics, Max Planck Society;

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Zitation

Mantiuk, R., Krawczyk, G., Mantiuk, R., & Seidel, H.-P. (2007). High Dynamic Range Imaging Pipeline: Perception-Motivated Representation of Visual Content. In B. E. Rogowitz, T. N. Pappas, & S. J. Daly (Eds.), Human Vision and Electronic Imaging XII (pp. 649212.1-12). Bellingham, WA, USA: SPIE.


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-000F-1F6A-B
Zusammenfassung
The advances in high dynamic range (HDR) imaging, especially in the display and camera technology, have a significant impact on the existing imaging systems. The assumptions of the traditional low-dynamic range imaging, designed for paper print as a major output medium, are ill suited for the range of visual material that is shown on modern displays. For example, the common assumption that the brightest color in an image is white can be hardly justified for high contrast LCD displays, not to mention next generation HDR displays, that can easily create bright highlights and the impression of self-luminous colors. We argue that high dynamic range representation can encode images regardless of the technology used to create and display them, with the accuracy that is only constrained by the limitations of the human eye and not a particular output medium. To facilitate the research on high dynamic range imaging, we have created a software package (http://pfstools.sourceforge.net/), capable of handling HDR data on all stages of image and video processing. The software package is available as open source under the General Public License and includes solutions for high quality image acquisition from multiple exposures, a range of tone mapping algorithms and a visual difference predictor for HDR images. We demonstrate how particular elements of the imaging pipeline can be interfaced using standard features of the operating system. Examples of shell scripts demonstrate how the software can be used for processing single images as well as video sequences.