The subjective test for compressed visual content is typically conducted by few experts called golden eyes. Here, we attempt to characterize the visual experience on JPEG-coded images of ordinary people statistically. To achieve this goal, a new image quality database, MCL-JCI, is constructed and introduced in this work. We explain the test procedure and conduct a preliminary analysis on test results. It is observed that people can only differentiate a finite number of quality levels and the perceived quality plot is a stair function of the coding bit rate. The relationship between the perceived quality plot and image content is discussed.
Lina Jin, Joe Yuchieh Lin, Sudeng Hu, Haiqiang Wang, Ping Wang, Ioannis Katsavounidis, Anne Aaron, C.-C. Jay Kuo, "Statistical Study on Perceived JPEG Image Quality via MCL-JCI Dataset Construction and Analysis" in Proc. IS&T Int’l. Symp. on Electronic Imaging: Image Quality and System Performance XIII, 2016, https://doi.org/10.2352/ISSN.2470-1173.2016.13.IQSP-222