[1] Seshadrinathan K, Soundararajan R, Bovik A C et al. Study of subjective and objective quality assessment of video[J]. IEEE Transactions on Image Processing, 19, 1427-1441(2010).
[2] Lin C T, Liu T J, Liu K H. Visual quality prediction on distorted stereoscopic images. [C]∥2017 IEEE International Conference on Image Processing (ICIP), September 17-20, 2017, Beijing, China. New York: IEEE, 3480-3484(2017).
[3] Lu W, He R, Yang J C et al. A spatiotemporal model of video quality assessment via 3D gradient differencing[J]. Information Sciences, 478, 141-151(2019).
[5] Mittal A, Saad M A, Bovik A C. A completely blind video integrity oracle[J]. IEEE Transactions on Image Processing, 25, 289-300(2016).
[6] Liu K H, Liu T J, Liu H H et al. Spatio-temporal interactive laws feature correlation method to video quality assessment. [C]∥2018 IEEE International Conference on Multimedia & Expo Workshops (ICMEW), July 23-27, 2018, San Diego, CA, USA. New York: IEEE, 18289260(2018).
[7] Choi L K, Bovik A C. Video quality assessment accounting for temporal visual masking of local flicker[J]. Signal Processing: Image Communication, 67, 182-198(2018).
[8] Søgaard J, Forchhammer S, Korhonen J. Video quality assessment and machine learning: performance and interpretability. [C]∥2015 Seventh International Workshop on Quality of Multimedia Experience (QoMEX), May 26-29, 2015, Pylos-Nestoras, Greece. New York: IEEE, 15260754(2015).
[9] Torres Vega M, Mocanu D C, Stavrou S et al. Predictive no-reference assessment of video quality[J]. Signal Processing: Image Communication, 52, 20-32(2017).
[10] Kim J, Zeng H, Ghadiyaram D et al. Deep convolutional neural models for picture-quality prediction: challenges and solutions to data-driven image quality assessment[J]. IEEE Signal Processing Magazine, 34, 130-141(2017).
[13] Seshadrinathan K, Bovik A C. Motion tuned spatio-temporal quality assessment of natural videos[J]. IEEE Transactions on Image Processing, 19, 335-350(2010).
[15] Simonyan K. -04-10)[2020-01-06]. https:∥arxiv., org/abs/1409, 1556(2015).
[16] Cho K, van Merrienboer B, Gulcehre C et al. -09-03)[2020-01-06]. https:∥arxiv., org/abs/1406, 1078(2014).
[17] Wu X, Du Z K, Guo Y K et al. Hierarchical attention based long short-term memory for Chinese lyric generation[J]. Applied Intelligence, 49, 44-52(2019).
[18] Boureau Y L, Bach F. LeCun Y, et al. Learning mid-level features for recognition. [C]∥2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, June 13-18, 2010, San Francisco, CA, USA. New York: IEEE, 2559-2566(2010).
[20] Duchi J, Hazan E, Singer Y. Adaptive subgradient methods for online learning and stochastic optimization[J]. Journal of Machine Learning Research, 12, 2121-2159(2011).
[21] Liu T J, Lin Y C, Lin W S et al. Visual quality assessment: recent developments, coding applications and future trends[J]. APSIPA Transactions on Signal and Information Processing, 2, e4(2013).
[22] Sánchez-Sinencio E. -09-01) https://www.researchgate.net/publication/303963853_LowPower_Multiplierless_YUVtoRGB_Converter_Based_on_Human_Vision_[2020-01-06]. Perception.(2009).
[23] Horé A, Ziou D. Image quality metrics: PSNR vs. SSIM. [C]∥2010 20th International Conference on Pattern Recognition, August 23-26, 2010, Istanbul, Turkey. New York: IEEE, 2366-2369(2010).
[24] Wang Z, Bovik A C, Sheikh H R et al. Image quality assessment: from error visibility to structural similarity[J]. IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society, 13, 600-612(2004).
[26] Janowski L, Malfait L, Pinson M H. Evaluating experiment design with unrepeated scenes for video quality subjective assessment[J]. Quality and User Experience, 4, 2(2019).