Yes / This work presents a methodology to optimize the selection of multiple parameter levels of an image acquisition,
degradation, or post-processing process applied to stimuli intended to be used in a subjective image or video
quality assessment (QA) study. It is known that processing parameters (e.g. compression bit-rate) or techni-
cal quality measures (e.g. peak signal-to-noise ratio, PSNR) are often non-linearly related to human quality
judgment, and the model of either relationship may not be known in advance. Using these approaches to select
parameter levels may lead to an inaccurate estimate of the relationship between the parameter and subjective
quality judgments – the system’s quality model. To overcome this, we propose a method for modeling the rela-
tionship between parameter levels and perceived quality distances using a paired comparison parameter selection
procedure in which subjects judge the perceived similarity in quality. Our goal is to enable the selection of evenly
sampled parameter levels within the considered quality range for use in a subjective QA study. This approach
is tested on two applications: (1) selection of compression levels for laparoscopic surgery video QA study, and
(2) selection of dose levels for an interventional X-ray QA study. Subjective scores, obtained from the follow-up
single stimulus QA experiments conducted with expert subjects who evaluated the selected bit-rates and dose
levels, were roughly equidistant in the perceptual quality space - as intended. These results suggest that a
similarity judgment task can help select parameter values corresponding to desired subjective quality levels. / Parts of this work were performed within the Telesurgery project (co-funded by iMinds, a digital research institute founded by the Flemish Government; project partners are Unilabs Teleradiology, SDNsquare and Barco, with project support from IWT) and the PANORAMA project (co-funded by grants from Belgium, Italy, France, the Netherlands, the United Kingdom, and the ENIAC Joint Undertaking).
| Identifer | oai:union.ndltd.org:BRADFORD/oai:bradscholars.brad.ac.uk:10454/16977 |
| Date | 16 March 2015 |
| Creators | Kumcu, A., Platisa, L., Chen, H., Gislason-Lee, Amber J., Davies, A.G., Schelkens, P., Taeymans, Y., Philips, W. |
| Source Sets | Bradford Scholars |
| Language | English |
| Detected Language | English |
| Type | Conference paper, Accepted manuscript |
| Rights | (c) 2015, Society of Photo-Optical Instrumentation Engineers (SPIE). This is an author produced version of a paper published in Proceedings of SPIE 9399, Image Processing: Algorithms and Systems XIII. |
Page generated in 0.0026 seconds