1. Remote expert viewing, laboratory tests or objective metrics: which one(s) to trust?
- Author
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Mathias Wien and Joel Jung
- Subjects
Visual quality assessment ,Quality metrics ,Remote expert viewing ,Visual media coding ,Electronics ,TK7800-8360 - Abstract
Abstract We present a study on the validity of quality assessment in the context of the development of visual media coding schemes. The work is motivated by the need for reliable means for decision-taking in standardization efforts of MPEG and JVET, i.e., the adoption or rejection of coding tools during the development process of the coding standard. The study includes results considering three means: objective quality metrics, remote expert viewing, which is a method designed in the context of MPEG standardization, and formal laboratory visual evaluation. The focus of this work is on the comparison of pairs of coded video sequences, e.g., a proposed change and an anchor scheme at a given rate point. An aggregation of performance measurements across multiple rate points, such as the Bjøntegaard Delta rate, is out of the scope of this paper. The paper details the test setup for the subjective assessment methods and the objective quality metrics under consideration. The results of the three approaches are reviewed, analyzed, and compared with respect to their suitability for the decision-taking task. The study indicates that, subject to the chosen test content and test protocols, the results of remote expert viewing using a forced-choice scale can be considered more discriminatory than the results of naïve viewers in the laboratory tests. The results further that, in general, the well-established quality metrics, such as PSNR, SSIM, or MS-SSIM, exhibit a high rate of correct decision-making when their results are compared with both types of viewing tests. Among the learning-based metrics, VMAF and AVQT appear to be most robust. For the development process of a coding standard, the selection of the most suitable means must be guided by the context, where a small number of carefully selected objective metrics, in combination with viewing tests for unclear cases, appears recommendable.
- Published
- 2024
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