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Conference object . 2009
Data sources: MPG.PuRe
https://doi.org/10.1117/12.809...
Article . 2009 . Peer-reviewed
Data sources: Crossref
DBLP
Conference object
Data sources: DBLP
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A perceptual evaluation of 3D unsharp masking

Authors: Matthias Ihrke; Tobias Ritschel 0001; Kaleigh Smith; Thorsten Grosch; Karol Myszkowski; Hans-Peter Seidel;

A perceptual evaluation of 3D unsharp masking

Abstract

Much research has gone into developing methods for enhancing the contrast of displayed 3D scenes. In the current study, we investigated the perceptual impact of an algorithm recently proposed by Ritschel et al.1 that provides a general technique for enhancing the perceived contrast in synthesized scenes. Their algorithm extends traditional image-based Unsharp Masking to a 3D scene, achieving a scene-coherent enhancement. We conducted a standardized perceptual experiment to test the proposition that a 3D unsharp enhanced scene was superior to the original scene in terms of perceived contrast and preference. Furthermore, the impact of different settings of the algorithm's main parameters enhancement-strength (λ) and gradient size (σ) were studied in order to provide an estimate of a reasonable parameter space for the method. All participants preferred a clearly visible enhancement over the original, non-enhanced scenes and the setting for objectionable enhancement was far above the preferred settings. The effect of the gradient size σ was negligible. The general pattern found for the parameters provides a useful guideline for designers when making use of 3D Unsharp Masking: as a rule of thumb they can easily determine the strength for which they start to perceive an enhancement and use twice this value for a good effect. Since the value for objectionable results was twice as large again, artifacts should not impose restrictions on the applicability of this rule.

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Average
Average
Average