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.
Subjective and objective visual quality assessment of images play 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.
Similarly, objective image quality metrics often exhibit limited correlation with subjective quality scores
across various distortion types and intensities, and little to no work has been devoted to assessing the
performance of these metrics on images with compression artifacts in the high to nearly visually lossless
quality range.
This talk discusses the effectiveness of both subjective and objective image quality assessment methods
on coding artifacts with higher visual quality. Moreover, ongoing solutions investigated in the context of
the JPEG AIC activity are presented.
Speaker(s): Michela Testolina,
Virtual: https://events.vtools.ieee.org/m/411480
This event has passed.
