Analysis of Public Image and Video Databases for Quality Assessment 论文

摘要

Databases of images or videos annotated with subjective ratings constitute essential ground truth for training, testing, and benchmarking algorithms for objective quality assessment. More than two dozen such databases are now available in the public domain; they are presented and analyzed in this paper. We propose several criteria for quantitative comparisons of source content, test conditions, and subjective ratings, which are used as the basis for the ensuing analyses and discussion. This information will allow researchers to make more well-informed decisions about databases, and may also guide the creation of additional test material and the design of future experiments.