Paper
9 February 2006 Lossy compression of high dynamic range images and video
Author Affiliations +
Proceedings Volume 6057, Human Vision and Electronic Imaging XI; 60570V (2006) https://doi.org/10.1117/12.639140
Event: Electronic Imaging 2006, 2006, San Jose, California, United States
Abstract
Most common image and video formats have been designed to work with existing output devices, like LCD or CRT monitors. As the display technology makes huge progress, these formats can no longer represent the data that the new devices can display. Therefore a shift towards higher precision image and video formats seems to be imminent. To overcome limitations of the common image and video formats, such as JPEG, PNG or MPEG, we propose a novel color space, which can accommodate an extended dynamic range and guarantees the precision that is below the visibility threshold. The proposed color space, which is derived from the contrast detection data, can represent the full range of luminance values and the complete color gamut that is visible to the human eye. We show that only minor changes are required to the existing encoding algorithms to accommodate a new color space and therefore greatly enhance information content of the visual data. We demonstrate this on two compression algorithms for High Dynamic Range (HDR) visual data: for static images and for video. We argue that the proposed HDR representation is a simple and universal way to encode visual data independently of the display or capture technology.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Rafał Mantiuk, Karol Myszkowski, and Hans-Peter Seidel "Lossy compression of high dynamic range images and video", Proc. SPIE 6057, Human Vision and Electronic Imaging XI, 60570V (9 February 2006); https://doi.org/10.1117/12.639140
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CITATIONS
Cited by 51 scholarly publications and 3 patents.
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KEYWORDS
High dynamic range imaging

Computer programming

Image compression

Video

Video compression

Visualization

Quantization

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