Crowdsourced Estimation of Collective Just Noticeable Difference for Compressed Video with the Flicker Test and QUEST+

dc.contributor.authorJenadeleh, Mohsen
dc.contributor.authorHamzaoui, Raouf
dc.contributor.authorReips, Ulf-Dietrich
dc.contributor.authorSaupe, Dietmar
dc.date.acceptance2024-05-14
dc.date.accessioned2024-06-12T10:20:28Z
dc.date.available2024-06-12T10:20:28Z
dc.date.issued2024-05-17
dc.descriptionThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
dc.description.abstractThe concept of videowise just noticeable difference (JND) was recently proposed for determining the lowest bitrate at which a source video can be compressed without perceptible quality loss with a given probability. This bitrate is usually obtained from estimates of the satisfied used ratio (SUR) at different encoding quality parameters. The SUR is the probability that the distortion corresponding to the quality parameter is not noticeable. Commonly, the SUR is computed experimentally by estimating the subjective JND threshold of each subject using a binary search, fitting a distribution model to the collected data, and creating the complementary cumulative distribution function of the distribution. The subjective tests consist of paired comparisons between the source video and compressed versions. However, as shown in this paper, this approach typically overestimates or underestimates the SUR. To address this shortcoming, we directly estimate the SUR function by considering the entire population as a collective observer. In our method, the subject for each paired comparison is randomly chosen, and a state-of-the-art Bayesian adaptive psychometric method (QUEST+) is used to select the compressed video in the paired comparison. Our simulations show that this collective method yields more accurate SUR results using fewer comparisons than traditional methods. We also perform a subjective experiment to assess the JND and SUR for compressed video. In the paired comparisons, we apply a flicker test that compares a video interleaving the source video and its compressed version with the source video. Analysis of the subjective data reveals that the flicker test provides, on average, greater sensitivity and precision in the assessment of the JND threshold than does the usual test, which compares compressed versions with the source video. Using crowdsourcing and the proposed approach, we build a JND dataset for 45 source video sequences that are encoded with both advanced video coding (AVC) and versatile video coding (VVC) at all available quantization parameters. Our dataset and the source code have been made publicly available at http://database.mmsp-kn.de/flickervidset-database.html.
dc.funderOther external funder (please detail below)
dc.funder.otherDFG
dc.identifier.citationM. Jenadeleh, R. Hamzaoui, U. -D. Reips and D. Saupe, (2024) Crowdsourced Estimation of Collective Just Noticeable Difference for Compressed Video with the Flicker Test and QUEST+. IEEE Transactions on Circuits and Systems for Video Technology, 34 (10), pp. 10135 - 10151
dc.identifier.doihttps://doi.org/10.1109/TCSVT.2024.3402363
dc.identifier.urihttps://hdl.handle.net/2086/23873
dc.language.isoen
dc.peerreviewedYes
dc.projectid496858717 and 51654672
dc.publisherIEEE
dc.researchinstituteInstitute of Engineering Sciences (IES)
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectJust noticeable difference
dc.subjectPsychometric function
dc.subjectSatisfied user ratio
dc.subjectFlicker test
dc.subjectSubjective quality assessment
dc.titleCrowdsourced Estimation of Collective Just Noticeable Difference for Compressed Video with the Flicker Test and QUEST+
dc.typeArticle

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