The Evolution of Video Quality Measurement: From PSNR to Hybrid Metrics

By Stefan Winkler, Praveen Mohandas. IEEE transactions on broadcasting, 2008

669 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/134986cbc54fb03900251e22d23e15b455abaf66

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Weisi Lin
2. Decebal Constantin Mocanu
3. Antonio Liotta
4. Jari Korhonen
5. Georgios Exarchakos
6. C.-C. Jay Kuo
7. Ke Gu
8. Guangtao Zhai

Citations in the corpus

• Two-Level Approach for No-Reference Consumer Video Quality Assessment (2019, methodology): “quality models have been classified into Full Reference (FR), Reduced Reference (RR) and No Reference (NR) models [29].”
• Deep learning for objective quality assessment of 3D images (2014, background): “This is in fact an open question in the Quality of Experience (QoE) literature [2, 3].”
• Perceptual visual quality metrics: A survey (2011, methodology): “In addition, end-to-end VPQMs would be useful by combining bitstream (without full decoding) and network loss analysis [183] for real-time, multi-channel quality monitoring (e.”