SCID: A database for screen content images quality assessment

Perceptual quality assessment of screen content images (S-CIs) has become a new challenging topic in the recent research of image quality assessment (IQA). In this work, we construct a new SCI database (called as SCID) for subjective quality evaluate of SCIs and investigate whether existing IQA models can effectively assess the perceptual quality of distorted SCIs. The proposed SCID, which is currently the largest one, containing 1,800 distorted SCIs generated from 40 reference SCIs with 9 types of distortions and 5 degradation levels for each distortion type. The double-stimulus impairment scale (DSIS) method is then employed to rate the perceptual quality, in which each image is evaluated by at least 40 assessors. After processing, each distorted SCI is accompanied with one mean opinion score (MOS) value to indicate its perceptual quality as ground truth. Based on the constructed S-CID, we evaluate the performances of 14 state-of-the-art IQA metrics. Experimental results show that the existing IQA metrics do not be able to evaluate the perceptual quality of SCIs well and an IQA metric specifically for SCIs is thus desirable. The proposed SCID will be made publicly available to the research community for further investigation on the perceptual processing of SCIs.