Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
The past decades have witnessed rapid growth in imaging as a major form of communication between individuals. Due to recent advances in capture, storage, delivery and display technologies, consumers demand improved perceptual quality while requiring reduced storage. In this context, research and innovation in lossy image compression have steered towards methods capable of achieving high compression ratios without compromising the perceived visual quality of images, and in some cases even enhancing the latter. Subjective visual quality assessment of images plays a fundamental role in defining quality as perceived by human observers. Although the field of image compression is constantly evolving towards efficient solutions for higher visual qualities, standardized subjective visual quality assessment protocols are still limited to those proposed in ITU-R Recommendation BT.500 and JPEG AIC standards. The number of comprehensive and in-depth studies where different protocols are compared is still insufficient. Moreover, previous works have not investigated the effectiveness of these methods on higher quality ranges, using recent image compression methods. In this paper, subjective visual scores collected from three subjective image quality assessment protocols, namely the Double Stimulus Continuous Quality Scale (DSCQS) and two test methods described in the JPEG AIC Part 2 standard, are compared between different laboratories under similar controlled conditions. The analysis of the experimental results has revealed that the DSCQS protocol is highly influenced by the quality of the reference images and experience of the subjects, while the JPEG AIC Part 2 specifications produce more stable results but are expensive and only suitable for a limited range of qualities. These emphasize the need for new robust subjective image quality assessment methodologies able to discriminate in the range of qualities generally demanded by consumers, i.e. from high to nearly visually lossless.
Touradj Ebrahimi, Michela Testolina, Davi Nachtigall Lazzarotto
Touradj Ebrahimi, Michela Testolina, Davi Nachtigall Lazzarotto, Vlad Hosu
Touradj Ebrahimi, Evgeniy Upenik, Michela Testolina