Blind image and video quality assessment
Images and videos are subject to a variety of distortions during acquisition, processing, compression, transmission, and reproduction. Designing objective image quality assessment methods are not only to monitor image quality degradation and to benchmark image processing systems but also to optimize many image processing algorithms and systems.
Humans are sensitive to image distortions and can effortlessly identify image distortions without any information about the pristine version. Developing objective methods to emulate this human ability is the main goal of blind or no-reference image quality assessment.