de.mpg.escidoc.pubman.appbase.FacesBean
Deutsch
 
Hilfe Wegweiser Datenschutzhinweis Impressum Kontakt
  DetailsucheBrowse

Datensatz

DATENSATZ AKTIONENEXPORT

Freigegeben

Konferenzbeitrag

Lossy compression of high dynamic range images and video

MPG-Autoren

Mantiuk,  Rafał
Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45095

Myszkowski,  Karol
Computer Graphics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45449

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

Externe Ressourcen
Es sind keine Externen Ressourcen verfügbar
Volltexte (frei zugänglich)
Es sind keine frei zugänglichen Volltexte verfügbar
Ergänzendes Material (frei zugänglich)
Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar
Zitation

Mantiuk, R., Myszkowski, K., & Seidel, H.-P. (2006). Lossy compression of high dynamic range images and video. In Human Vision and Electronic Imaging XI. Bellingham, USA: SPIE.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-000F-235C-8
Zusammenfassung
Most common image and video formats have been designed to work with existing output devices, like LCD or CRT monitors. As display technology makes progress, these formats no longer represent the data that new devices can display. Therefore a shift towards higher precision image and video formats is imminent. To overcome limitations of 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 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 the new color space and therefore greatly enhance information content of the visual data. We demonstrate this with 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 independent of the display or capture technology.