English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Conference Paper

Predicting Visible Differences in High Dynamic Range Images - Model and its Calibration

MPS-Authors
/persons/resource/persons44986

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

/persons/resource/persons45095

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

/persons/resource/persons45449

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

External Resource
No external resources are shared
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
Citation

Mantiuk, R., Daly, S., Myszkowski, K., & Seidel, H.-P. (2005). Predicting Visible Differences in High Dynamic Range Images - Model and its Calibration. In Human Vision and Electronic Imaging X, IS&T/SPIE's 17th Annual Symposium on Electronic Imaging (2005) (pp. 204-214). Bellingham, USA: SPIE.


Cite as: https://hdl.handle.net/11858/00-001M-0000-000F-2773-0
Abstract
New imaging and rendering systems commonly use physically accurate lighting information in the form of high-dynamic range (HDR) images and video. HDR images contain actual colorimetric or physical values, which can span 14 orders of magnitude, instead of 8-bit renderings, found in standard images. The additional precision and quality retained in HDR visual data is necessary to display images on advanced HDR display devices, capable of showing contrast of 50,000:1, as compared to the contrast of 700:1 for LCD displays. With the development of high-dynamic range visual techniques comes a need for an automatic visual quality assessment of the resulting images. In this paper we propose several modifications to the Visual Difference Predicator (VDP). The modifications improve the prediction of perceivable differences in the full visible range of luminance and under the adaptation conditions corresponding to real scene observation. The proposed metric takes into account the aspects of high contrast vision, like scattering of the light in the optics (OTF), nonlinear response to light for the full range of luminance, and local adaptation. To calibrate our HDR~VDP we perform experiments using an advanced HDR display, capable of displaying the range of luminance that is close to that found in real scenes.