Abstract
Even with modern graphics hardware, it is still not
possible to achieve high fidelity renderings of complex
scenes in real time. However, as these images are
produced for human observers we may exploit the fact
that the human eye is good, but not that good. In
particular, it may be possible to render parts of an
image at high quality and the rest of the scene at lower
quality without the user being aware of this difference.
Image quality assessment algorithms, such as the Daly
model, provide a measure of the perceptual quality
difference between image pairs. This paper presents a
psychophysical evaluation of an image quality metric
and investigates how such models can be developed to
rapidly determine the parts of the scene with the most
noticeable perceptual difference.
Translated title of the contribution | User Validation of Image Quality Assessment Algorithms |
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Original language | English |
Title of host publication | Unknown |
Publisher | IEEE Computer Society |
Pages | 196 - 202 |
Number of pages | 6 |
ISBN (Print) | 0769521371 |
Publication status | Published - Jun 2004 |