No-reference image and video quality estimation: Applications and human-motivated design

Abstract

This paper reviews the basic background knowledge necessary to design effective no-reference (NR) quality estimators (QEs) for images and video. We describe a three-stage framework for NR QE that encompasses the range of potential use scenarios for the NR QE and allows knowledge of the human visual system to be incorporated throughout. We survey the measurement stage of the framework, considering methods that rely on bitstream, pixels, or both. By exploring both the accuracy requirements of potential uses as well as evaluation criteria to stress-test a QE, we set the stage for our community to make substantial future improvements to the challenging problem of NR quality estimation.