Quality measures of reconstruction filters for stereoscopic volume rendering

Roberts, David A.T.; Ivrissimtzis, Ioannis

doi:10.1007/s41095-016-0035-7

Quality measures of reconstruction filters for stereoscopic volume rendering

Roberts, David A.T.; Ivrissimtzis, Ioannis

Authors

David A.T. Roberts

Dr Ioannis Ivrissimtzis ioannis.ivrissimtzis@durham.ac.uk
Associate Professor

Abstract

In direct volume rendering (DVR), the choice of reconstruction filter can have a significant effect on the visual appearance of the images produced and thus, on the perceived quality of a DVR rendered scene. This paper presents the results of a subjective experiment where participants stereoscopically viewed DVR rendered scenes and rated their subjective quality. The statistical analysis of the results focuses on the relationship between the quality of the stereoscopic scene and properties of the filters such as post-aliasing and smoothing, as well as the relationship between the quality of the stereoscopic scene and properties of the rendered images such as shape compactness. The experiment evaluated five reconstruction filters on four different volumetric datasets. Participants rated the stereoscopic scenes on four quality measures: depth quality, depth layout, lack of jaggyness, and sharpness. The results show that the correlation between the quality measures and post-aliasing and smoothing, which are properties associated with each reconstruction filter, is moderate and statistically insignificant. On the other hand, the correlation between the quality measures and compactness, which is a property specific to each rendered image, is strong and statistically significant.

Citation

Roberts, D. A., & Ivrissimtzis, I. (2016). Quality measures of reconstruction filters for stereoscopic volume rendering. Computational Visual Media, 2(1), 19-30. https://doi.org/10.1007/s41095-016-0035-7

Journal Article Type	Article
Acceptance Date	Dec 9, 2015
Online Publication Date	Jan 29, 2016
Publication Date	Mar 1, 2016
Deposit Date	Feb 1, 2016
Publicly Available Date	Feb 26, 2016
Journal	Computational Visual Media
Print ISSN	2096-0433
Publisher	SpringerOpen
Peer Reviewed	Peer Reviewed
Volume	2
Issue	1
Pages	19-30
DOI	https://doi.org/10.1007/s41095-016-0035-7

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