MCL lab is proud to release a new dataset about compressed images. It consists of 50 source images with resolution 1920×1080 and 100 JPEG-coded images for each source image. More than 150 volunteers participated in the subjective test. Each individual set of compressed images was evaluated by 30 subjects in a controlled environment.

This dataset was proposed to challenge the traditional approaches to measure the quality of compressed image/video. Based on the characteristics of the Human Visual System (HVS), a Just Noticeable Difference (JND) framework was proposed to investigate the limitation of HVS on compressed images. It means to boost large-scale statistical study on human-perceived image quality as well as the future development of perceptual-based image/video coding standards.