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Study of subjective and objective quality assessment for screen content images

In this paper, we present the results of a recent large-scale subjective study of image quality on a collection of screen contents distorted by a variety of application-relevant processes. With the development of multi-device interactive multimedia applications, metrics to predict the visual quality of screen content images (SCIs) as perceived by subjects are becoming fundamentally important. For developing the objective image quality assessment (IQA) method, there is a need for large-scale public database with diversity of distorted types and scene contents, and available subjective scores of distorted SCIs. The resulting Immersive Media Laboratory screen content image quality database (IML-SCIQD) contains 1250 distorted SCIs from 25 reference SCIs with 10 distortion types. Each image was rated by 35 human observers, and the different mean opinion scores (DMOS) were obtained after data processing. The performance comparison of 17 state-of-the-arts, publicly available IQA algorithms are evaluated on the new database. The database will be available online in our project website.