Jour Fixe: "JND-based perceptual quality assessment of nearly lossless compressed visual media"

The Zukunftskolleg invited everyone to the jour fixe led by Mohsen Jenadeleh (former Associated Fellow / Computer and Information Science).

Mohsen Jenadeleh (former Associated Fellow / Computer and Information Science) gave a talk entitled "JND-based perceptual quality assessment of nearly lossless compressed visual media".

Abstract:

Perceptual quality assessment has been a long-standing problem that attracts attention from both academia and industry. The just-noticeable-difference (JND) methodology has been proposed to measure the human subjective quality of experience in recent years. In this talk, I will provide a brief review of JND-based visual quality measurement and its applications. I will also discuss the biases introduced by current methodologies for subjective JND assessment and introduce a methodology to collectively assess the JND and address the bias problem. During this talk, I will explore ways to optimize the JND subjective test methodology in the context of video compression, aiming to estimate user satisfaction with a given video quality at a lower cost and with higher accuracy using both simulations and human studies. Experimental results will be presented to demonstrate the performance of the proposed methods.

Literature:

1- Jenadeleh, Mohsen, Raouf Hamzaoui, Ulf-Dietrich Reips, and Dietmar Saupe. "Crowdsourced Estimation of Collective Just Noticeable Difference for Compressed Video with Flicker Test and QUEST+." (2023).

2- Jenadeleh, Mohsen, Johannes Zagermann, Harald Reiterer, Ulf-Dietrich Reips, Raouf Hamzaoui, and Dietmar Saupe, "Relaxed Forced Choice Improves Performance of Visual Quality Assessment Methods," 2023 15th International Conference on Quality of Multimedia Experience (QoMEX), Ghent, Belgium, 2023, pp. 37-42 (nominated as one of the 5 candidates for the best paper award).

3- Testolina, Michela, Vlad Hosu, Mohsen Jenadeleh, Davi Lazzarotto, Dietmar Saupe, and Touradj Ebrahimi. "JPEG AIC-3 Dataset: Towards Defining the High Quality to Nearly Visually Lossless Quality Range." In 2023 15th International Conference on Quality of Multimedia Experience (QoMEX), pp. 55-60. IEEE, 2023 (won the best  student paper award).