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This paper presents a new image database, SSID, which provides images for evaluation and design of visual quality assessment metrics. It currently contains 1,688 images, 8 reference images, 7 types of distortions per reference image and 30 applications of the distortion types with varying parameters. The distortion types address image errors arising in visual compositions of real and synthetic content, thus provide a basis for visual quality assessment metrics targeting augmented realities and other scenarios where synthetic objects are added to existing scenes. In over 17,000 subjective experiments Mean Opinion Scores for the database have been obtained. These MOS can assist the evaluation of existing and design of novel image quality metrics for scenarios including synthetic content. The evaluation of several existing and widely used quality metrics on the SSID database is included in this paper. The database is made freely available, reproducible and extendable for further scientific research.

Saarbrucken Synthetic Image Database - An Image Database for Design and Evaluation of Visual Quality Metrics in Synthetic Scenarios