[1] G T ZHAI, X K MIN. Perceptual image quality assessment： a survey. Science China Information Sciences, 63, 1-52(2020).

[2] [2] 2弓殷强， 余新， 邱国平. 显示设备环境自适应色调映射算法［J］. 液晶与显示， 2021， 36（12）： 1645-1657. doi: 10.37188/cjlcd.2021-0100GONGY Q， YUX， QIUG P. Environment adaptive tone mapping algorithm for display devices［J］. Chinese Journal of Liquid Crystals and Displays， 2021， 36（12）： 1645-1657.（in Chinese）. doi: 10.37188/cjlcd.2021-0100

[3] S CHENG, H ZENG, J CHEN et al. Screen content video quality assessment： subjective and objective study. IEEE Transactions on Image Processing： a Publication of the IEEE Signal Processing Society(2020).

[4] J Y YAO, G Z LIU. Bitrate-based no-reference video quality assessment combining the visual perception of video contents. IEEE Transactions on Broadcasting, 65, 546-557(2019).

[5] H P MARGARET. The consumer digital video library. Available. https：//www.cdvl.org/

[6] M PEREZ-ORTIZ, A MIKHAILIUK, E ZERMAN et al. From pairwise comparisons and rating to a unified quality scale. IEEE Transactions on Image Processing： a Publication of the IEEE Signal Processing Society, 2019(2019).

[7] Q FAN, W LUO, Y XIA et al. Metrics and methods of video quality assessment： a brief review. Multimedia Tools and Applications, 78, 31019-31033(2019).

[8] E CEMILOGLU, G N YILMAZ. Blind video quality assessment via spatiotemporal statistical analysis of adaptive cube size 3D-DCT coefficients. IET Image Processing, 14, 845-852(2020).

[9] S MITRA, R SOUNDARARAJAN, S S CHANNAPPAYYA. Predicting spatio-temporal entropic differences for robust no reference video quality assessment. IEEE Signal Processing Letters, 28, 170-174(2021).

[10] G KULUPANA, D S TALAGALA, H K ARACHCHI et al. End user video quality prediction and coding parameters selection at the encoder for robust HEVC video transmission. IEEE Transactions on Circuits and Systems for Video Technology, 29, 3367-3381(2019).

[11] Z B CHEN, N LIAO, X D GU et al. Hybrid distortion ranking tuned bitstream-layer video quality assessment. IEEE Transactions on Circuits and Systems for Video Technology, 26, 1029-1043(2016).

[12] M A USMAN, M R USMAN, S Y SHIN. A novel no-reference metric for estimating the impact of frame freezing artifacts on perceptual quality of streamed videos. IEEE Transactions on Multimedia, 20, 2344-2359(2018).

[13] P F CHEN, L D LI, L MA et al. RIRNet： recurrent-in-recurrent network for video quality assessment, 834-842(2020).

[14] M BANITALEBI-DEHKORDI, A EBRAHIMI-MOGHADAM, M KHADEMI et al. No-reference quality assessment of HEVC video streams based on visual memory modelling. Journal of Visual Communication and Image Representation, 75, 103011(2021).

[15] Y ZHANG, D M CHANDLER. Opinion-unaware blind quality assessment of multiply and singly distorted images via distortion parameter estimation. IEEE Transactions on Image Processing, 27, 5433-5448(2018).

[16] L FOTIO TIOTSOP, T MIZDOS, M UHRINA et al. Modeling and estimating the subjects’ diversity of opinions in video quality assessment： a neural network based approach. Multimedia Tools and Applications, 80, 3469-3487(2021).

[17] W J ZOU, F Z YANG, J R SONG et al. Event-based perceptual quality assessment for HTTP-based video streaming with playback interruption. IEEE Transactions on Multimedia, 20, 1475-1488(2018).

[18] A AHAR, A BARRI, P SCHELKENS. From sparse coding significance to perceptual quality： a new approach for image quality assessment. IEEE Transactions on Image Processing, 27, 879-893(2018).

[19] S H CHOI, H KIM, K C SHIN et al. Perceived color impression for spatially mixed colors. Journal of Display Technology, 10, 282-287(2014).

[20] J C LIU, Y GENG, D Y WANG et al. An objective multi-factor QoE evaluation based on content classification for H.264/AVC encoded video, 137-142.

[21] [21] 21范赐恩， 冉杰文， 颜佳， 等. 颜色空间统计联合纹理特征的无参考图像质量评价［J］. 光学 精密工程， 2018， 26（4）： 916-926. doi: 10.3788/ope.20182604.0916FANC E， RANJ W， YANJ， et al. No-reference image quality assessment using joint color space statistical and texture feature［J］. Opt. Precision Eng.， 2018， 26（4）： 916-926.（in Chinese）. doi: 10.3788/ope.20182604.0916

[22] X W SHANG, J LIANG, G Z WANG et al. Color-sensitivity-based combined PSNR for objective video quality assessment. IEEE Transactions on Circuits and Systems for Video Technology, 29, 1239-1250(2019).

[23] B J WHITE, D KERZEL, K R GEGENFURTNER. The spatio-temporal tuning of the mechanisms in the control of saccadic eye movements. Vision Research, 46, 3886-3897(2006).

[24] H R SHEIKH, Z WANG, A C BOVIK. LIVE image and video quality assessment database. http：//live.ece.utexas.edu/ research/quality

[25] M ÇALı, N ÖZBEK. SSIM-based adaptation for DASH with SVC in mobile networks. Signal， Image and Video Processing, 14, 1107-1114(2020).

[26] J FARRELL, M OKINCHA, M PARMAR et al. Using visible SNR （vSNR） to compare the image quality of pixel binning and digital resizing, 7537, 106-114(2010).

[27] J KORHONEN. Two-level approach for no-reference consumer video quality assessment. IEEE Transactions on Image Processing： a Publication of the IEEE Signal Processing Society, 28, 5923-5938(2019).

[28] S DENDI, S S CHANNAPPAYYA. No-reference video quality assessment using natural spatiotemporal scene statistics. IEEE Transactions on Image Processing： a Publication of the IEEE Signal Processing Society, 2020(2020).

[29] Q B WU, H L LI, F M MENG et al. Toward a blind quality metric for temporally distorted streaming video. IEEE Transactions on Broadcasting, 64, 367-378(2018).

[30] X L LI, Q GUO, X Q LU. Spatiotemporal statistics for video quality assessment. IEEE Transactions on Image Processing, 25, 3329-3342(2016).

[31] I DE PONTES OLIVEIRA et al. Design of objective video quality metrics using spatial and temporal informations. IEEE Latin America Transactions, 13, 790-795(2015).

[32] Z Y GUAN, H Z LV, Y MA et al. A novel objective quality assessment method for video conferencing coding. China Communications, 16, 89-104(2019).

[33] A KUMCU, K BOMBEKE, L PLATIŠA et al. Performance of four subjective video quality assessment protocols and impact of different rating preprocessing and analysis methods. IEEE Journal of Selected Topics in Signal Processing, 11, 48-63(2017).

[34] P F CHEN, L D LI, J J WU et al. Temporal reasoning guided QoE evaluation for mobile live video broadcasting. IEEE Transactions on Image Processing： a Publication of the IEEE Signal Processing Society, 30, 3279-3292(2021).

[35] D Q LI, T T JIANG, M JIANG. Quality assessment of in-the-wild videos, 2351-2359(2019).

[36] [36] 36马畅， 张选德. 基于颜色名称的彩色图像质量评价［J］. 液晶与显示， 2022， 37（1）： 56-65. doi: 10.37188/CJLCD.2021-0189MAC， ZHANGX D. Color image quality assessment based on colornames［J］. Chinese Journal of Liquid Crystals and Displays， 2022， 37（1）： 56-65.（in Chinese）. doi: 10.37188/CJLCD.2021-0189

[37] [37] 37姚军财， 申静， 黄陈蓉. 基于多层BP神经网络的无参考视频质量客观评价［J］. 自动化学报， 2022， 48（2）： 594-607. doi: 10.16383/j.aas.c190539YAOJ C， SHENJ， HUANGCH R. No reference video quality objective assessment based on multilayer BP neural network［J］. Acta Automatica Sinica， 2022， 48（2）： 594-607.（in Chinese）. doi: 10.16383/j.aas.c190539

[38] L H CHEN, C G BAMPIS, Z LI et al. Perceptual video quality prediction emphasizing chroma distortions. IEEE Transactions on Image Processing, 30, 1408-1422(2021).