  Research on image quality assessment (IQA) remains limited mainly due to our
incomplete knowledge about human visual perception. Existing IQA algorithms
have been designed or trained with insufficient subjective data with a small
degree of stimulus variability. This has led to challenges for those algorithms
to handle complexity and diversity of real-world digital content. Perceptual
evidence from human subjects serves as a grounding for the development of
advanced IQA algorithms. It is thus critical to acquire reliable subjective
data with controlled perception experiments that faithfully reflect human
behavioural responses to distortions in visual signals. In this paper, we
present a new study of image quality perception where subjective ratings were
collected in a controlled lab environment. We investigate how quality
perception is affected by a combination of different categories of images and
different types and levels of distortions. The database will be made publicly
available to facilitate calibration and validation of IQA algorithms.
