A Database and Model for the Visual Quality Assessment of Super-Resolution Videos

• Published in: IEEE transactions on broadcasting Vol. 70; no. 2; pp. 516 - 532
• Main Authors: Zhou, Fei, Sheng, Wei, Lu, Zitao, Qiu, Guoping
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.06.2024; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Artificial neural networks; Data analysis; Display devices; Evaluation; Feature extraction; Quality assessment; Quality assurance; Quality enhancement assessment; Spatial resolution; super-resolution video quality assessment; Superresolution; Video; video database; Videos; Viewing; Visualization
• ISSN: 0018-9316; 1557-9611
• DOI: 10.1109/TBC.2024.3382949

Video super-resolution (SR) has important real world applications such as enhancing viewing experiences of legacy low-resolution videos on high resolution display devices. However, there are no visual quality assessment (VQA) models specifically designed for evaluating SR videos while such models ar...