Abstract

We designed and created a new image quality database that models diverse authentic image distortions and artifacts that affect images that are captured using modern mobile devices. We also designed and implemented a new online crowdsourcing system, which we are using to conduct a very large-scale, on-going, multi-month image quality assessment (IQA) subjective study, wherein a wide range of diverse observers record their judgments of image quality. Our database currently consists of over 320,000 opinion scores on 1,163 authentically distorted images evaluated by over 7000 human observers. The new database will soon be made freely available for download and we envision that the fruits of our efforts will provide researchers with a valuable tool to benchmark and improve the performance of objective IQA algorithms.

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