Comparison of Four Subjective Methods for Image Quality Assessment

dc.contributor.authorMantiuk, Rafał K.en_US
dc.contributor.authorTomaszewska, Annaen_US
dc.contributor.authorMantiuk, Radosławen_US
dc.contributor.editorHolly Rushmeier and Oliver Deussenen_US
dc.date.accessioned2015-02-28T08:23:25Z
dc.date.available2015-02-28T08:23:25Z
dc.date.issued2012en_US
dc.description.abstractTo provide a convincing proof that a new method is better than the state of the art, computer graphics projects are often accompanied by user studies, in which a group of observers rank or rate results of several algorithms. Such user studies, known as subjective image quality assessment experiments, can be very time‐consuming and do not guarantee to produce conclusive results. This paper is intended to help design efficient and rigorous quality assessment experiments and emphasise the key aspects of the results analysis. To promote good standards of data analysis, we review the major methods for data analysis, such as establishing confidence intervals, statistical testing and retrospective power analysis. Two methods of visualising ranking results together with the meaningful information about the statistical and practical significance are explored. Finally, we compare four most prominent subjective quality assessment methods: single‐stimulus, double‐stimulus, forced‐choice pairwise comparison and similarity judgements. We conclude that the forced‐choice pairwise comparison method results in the smallest measurement variance and thus produces the most accurate results. This method is also the most time‐efficient, assuming a moderate number of compared conditions.To provide a convincing proof that a new method is better than the state‐of‐the‐art, computer graphics projects are often accompanied by user studies, in which a group of observers rank or rate results of several algorithms. Such user studies, known as subjective image quality assessment experiments, can be very time consuming and do not guarantee to produce conclusive results. This paper is intended to help design efficient and rigorous quality assessment experiments and emphasise the key aspects of the results analysis.en_US
dc.description.number8
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume31
dc.identifier.doi10.1111/j.1467-8659.2012.03188.x
dc.identifier.issn1467-8659en_US
dc.identifier.urihttps://doi.org/10.1111/j.1467-8659.2012.03188.xen_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltd.en_US
dc.titleComparison of Four Subjective Methods for Image Quality Assessmenten_US
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