5.3.10.11 Video Quality, Video Image Quality Evaluations

Chapter Contents (Back)
Evaluation, Video. Video Quality. For compressed video:
See also Video Quality for Compression, Coded Video.
See also Video Quality for Stereo, 3D Video.
See also General Rate-Quality, Rate Distortion, Rate Control, Error Tradeoffs for Video.

Aldridge, R.P.[Richard P.], Pearson, D.E.[Don E.],
A calibration method for continuous video quality (SSCQE) measurements,
SP:IC(16), No. 3, October 2000, pp. 321-332.
Elsevier DOI 0010
BibRef

Le Clerc, F.[Francois],
Method for estimating the noise level in a video sequence,
US_Patent6,307,888, Oct 23, 2001
WWW Link. BibRef 0110

Winkler, S.,
Issues in vision modeling for perceptual video quality assessment,
SP(78), No. 2, 1999, pp. 231-252. BibRef 9900

Cavallaro, A., Winkler, S.,
Segmentation-driven perceptual quality metrics,
ICIP04(V: 3543-3546).
IEEE DOI 0505
BibRef

Sanchez-Marin, F.J., Srinivas, Y., Jabri, K.N.[Kadri N.], Wilson, D.L.[David L.],
Quantitative image quality analysis of a nonlinear spatio-temporal filter,
IP(10), No. 2, February 2001, pp. 288-295.
IEEE DOI 0104
BibRef

Watson, A.B.[Andrew B.],
Method and apparatus for evaluating the visual quality of processed digital video sequences,
US_Patent6,493,023, Dec 10, 2002
WWW Link. BibRef 0212

Jabri, K.N.[Kadri N.], Wilson, D.L.[David L.],
Quantitative assessment of image quality enhancement due to unsharp-mask processing in x-ray fluoroscopy,
JOSA-A(19), No. 7, July 2002, pp. 1297-1307.
DOI Link 0208
BibRef

Hekstra, A.P., Beerends, J.G., Ledermann, D., de Caluwe, F.E., Kohler, S., Koenen, R.H., Rihs, S., Ehrsam, M., Schlauss, D.,
PVQM: A perceptual video quality measure,
SP:IC(17), No. 10, November 2002, pp. 781-798.
Elsevier DOI 0211
BibRef

Wang, Z.[Zhou], Lu, L.G.[Li-Gang], Bovik, A.C.[Alan C.],
Video quality assessment based on structural distortion measurement,
SP:IC(19), No. 2, February 2004, pp. 121-132.
Elsevier DOI 0401
BibRef
Earlier:
Video quality assessment using structural distortion measurement,
ICIP02(III: 65-68).
IEEE DOI 0210
BibRef
Earlier: A1, A3, A2:
Wavelet-based Foveated Image Quality Measurement for Region of Interest Image Coding,
ICIP01(II: 89-92).
IEEE DOI 0108
BibRef

Lee, D.Y.[Dae Yeol], Paul, S.[Somdyuti], Bampis, C.G.[Christos G.], Ko, H.[Hyunsuk], Kim, J.H.[Jong-Ho], Jeong, S.Y.[Se Yoon], Homan, B.[Blake], Bovik, A.C.[Alan C.],
A Subjective and Objective Study of Space-Time Subsampled Video Quality,
IP(31), 2022, pp. 934-948.
IEEE DOI 2201
Streaming media, Image coding, Video recording, Quality assessment, Spatial resolution, Bit rate, Spatial databases, video quality assessment BibRef

Lee, D.Y.[Dae Yeol], Kim, J.[Jongho], Ko, H.[Hyunsuk], Bovik, A.C.[Alan C.],
Video Quality Model of Compression, Resolution and Frame Rate Adaptation Based on Space-Time Regularities,
IP(31), 2022, pp. 3644-3656.
IEEE DOI 2206
Streaming media, Video recording, Quality assessment, Predictive models, Image coding, Distortion, Video compression, video compression BibRef

Lu, Z.K.[Zhong-Kang], Lin, W.S., Yang, X.K., Ong, E.P., Yao, S.[Susa],
Modeling Visual Attention's Modulatory Aftereffects on Visual Sensitivity and Quality Evaluation,
IP(14), No. 11, November 2005, pp. 1928-1942.
IEEE DOI 0510
BibRef
Earlier: A1, A3, A2, A4, A5:
Modelling visual attention and motion effect for visual quality evaluation,
ICIP04(IV: 2311-2314).
IEEE DOI 0505
BibRef

Yang, F.Z.[Fu-Zheng], Wan, S.A.[Shu-Ai], Chang, Y.L.[Yi-Lin], Wu, H.R.[Hong Ren],
A novel objective no-reference metric for digital video quality assessment,
SPLetters(12), No. 10, October 2005, pp. 685-688.
IEEE DOI 0510
BibRef

Masry, M., Hemami, S.S., Sermadevi, Y.,
A scalable wavelet-based video distortion metric and applications,
CirSysVideo(16), No. 2, February 2006, pp. 260-273.
IEEE DOI 0604

See also Convex Programming Formulations for Rate Allocation in Video Coding. BibRef

Bordes, P.[Philippe], Guillotel, P.[Philippe],
Process, device and use for evaluating coded images,
US_Patent7,003,037, Feb 21, 2006
WWW Link. BibRef 0602

Gu, K.[Ke], Zhai, G.T.[Guang-Tao], Yang, X.K.[Xiao-Kang], Zhang, W.J.[Wen-Jun],
Using Free Energy Principle For Blind Image Quality Assessment,
MultMed(17), No. 1, January 2015, pp. 50-63.
IEEE DOI 1502
Gaussian distribution
See also Psychovisual Quality Metric in Free-Energy Principle, A.
See also Reduced-Reference Image Quality Assessment in Free-Energy Principle and Sparse Representation. BibRef

Gu, K.[Ke], Zhai, G.T.[Guang-Tao], Lin, W.S.[Wei-Si], Yang, X.K.[Xiao-Kang], Zhang, W.J.[Wen-Jun],
Visual Saliency Detection With Free Energy Theory,
SPLetters(22), No. 10, October 2015, pp. 1552-1555.
IEEE DOI 1506
filtering theory BibRef

Gu, K.[Ke], Zhai, G.T.[Guang-Tao], Lin, W.S.[Wei-Si], Yang, X.K.[Xiao-Kang], Zhang, W.J.[Wen-Jun],
No-Reference Image Sharpness Assessment in Autoregressive Parameter Space,
IP(24), No. 10, October 2015, pp. 3218-3231.
IEEE DOI 1507
Brain modeling BibRef

Mei, T., Hua, X.S., Zhu, C.Z., Zhou, H.Q., Li, S.,
Home Video Visual Quality Assessment With Spatiotemporal Factors,
CirSysVideo(17), No. 6, June 2007, pp. 699-706.
IEEE DOI 0706
BibRef

Chen, J.Y.C., Thropp, J.E.,
Review of Low Frame Rate Effects on Human Performance,
SMC-A(37), No. 6, November 2007, pp. 1063-1076.
IEEE DOI 0709
BibRef

Akcakaya, M., Tarokh, V.,
Performance of Sparse Representation Algorithms Using Randomly Generated Frames,
SPLetters(14), No. 11, November 2007, pp. 777-780.
IEEE DOI 0709
BibRef

Akcakaya, M., Tarokh, V.,
Sparse Signal Recovery from a Mixture of Linear and Magnitude-Only Measurements,
SPLetters(22), No. 9, September 2015, pp. 1220-1223.
IEEE DOI 1503
compressed sensing BibRef

Wang, Z.[Zhou], Li, Q.A.[Qi-Ang],
Video quality assessment using a statistical model of human visual speed perception,
JOSA-A(24), No. 12, December 2007, pp. B61-B69.
DOI Link 0801
BibRef

Irie, K.[Kazunari], McKinnon, A.E., Unsworth, K., Woodhead, I.M.,
A Technique for Evaluation of CCD Video-Camera Noise,
CirSysVideo(18), No. 2, February 2008, pp. 280-284.
IEEE DOI 0803
BibRef

Seshadrinathan, K.[Kalpana], Bovik, A.C.[Alan C.],
Motion Tuned Spatio-Temporal Quality Assessment of Natural Videos,
IP(19), No. 2, February 2010, pp. 335-350.
IEEE DOI 1002
BibRef
Earlier:
Unifying Analysis of Full Reference Image Quality Assessment,
ICIP08(1200-1203).
IEEE DOI 0810

See also Statistical Evaluation of Recent Full Reference Image Quality Assessment Algorithms, A. BibRef

Kim, W., Nguyen, A., Lee, S., Bovik, A.C.[Alan C.],
Dynamic Receptive Field Generation for Full-Reference Image Quality Assessment,
IP(29), 2020, pp. 4219-4231.
IEEE DOI 2002
Full-reference image quality assessment (FR-IQA), dynamic receptive fields (DRFs), human visual system (HVS) BibRef

Soundararajan, R., Bovik, A.C.,
Video Quality Assessment by Reduced Reference Spatio-Temporal Entropic Differencing,
CirSysVideo(23), No. 4, April 2013, pp. 684-694.
IEEE DOI 1304

See also RRED Indices: Reduced Reference Entropic Differencing for Image Quality Assessment. BibRef

Mitra, S., Soundararajan, R., Channappayya, S.S.,
Predicting Spatio-Temporal Entropic Differences for Robust No Reference Video Quality Assessment,
SPLetters(28), 2021, pp. 170-174.
IEEE DOI 2102
Indexes, Distortion, Streaming media, Quality assessment, Databases, Video recording, Prediction algorithms, spatio-temporal reduced reference entropic difference (ST-RRED) BibRef

Moorthy, A.K., Seshadrinathan, K., Soundararajan, R., Bovik, A.C.,
Wireless Video Quality Assessment: A Study of Subjective Scores and Objective Algorithms,
CirSysVideo(20), No. 4, April 2010, pp. 587-599.
IEEE DOI 1003
BibRef

Moorthy, A.K., Bovik, A.C.,
Efficient Video Quality Assessment Along Temporal Trajectories,
CirSysVideo(20), No. 11, November 2010, pp. 1653-1658.
IEEE DOI 1011
BibRef

Seshadrinathan, K.[Kalpana], Soundararajan, R., Bovik, A.C.[Alan C.], Cormack, L.K.,
Study of Subjective and Objective Quality Assessment of Video,
IP(19), No. 6, June 2010, pp. 1427-1441.
IEEE DOI 1006
BibRef

Min, X., Zhai, G., Zhou, J., Farias, M.C.Q., Bovik, A.C.,
Study of Subjective and Objective Quality Assessment of Audio-Visual Signals,
IP(29), 2020, pp. 6054-6068.
IEEE DOI 2005
Streaming media, Distortion, Databases, Quality assessment, Quality of experience, Video recording, Predictive models, multimodal fusion BibRef

Yim, C.H.[Chang-Hoon], Bovik, A.C.[Alan C.],
Evaluation of temporal variation of video quality in packet loss networks,
SP:IC(26), No. 1, January 2011, pp. 24-38.
Elsevier DOI 1101
Video communication; Wireless network; Channel error; Quality assessment; Quality variation BibRef

Lee, K.H.[Kwang-Hyun], Park, J.[Jincheol], Lee, S.H.[Sang-Hoon], Bovik, A.C.[Alan C.],
Temporal pooling of video quality estimates using perceptual motion models,
ICIP10(2493-2496).
IEEE DOI 1009
BibRef

Garcia, J.A., Rodriguez-Sanchez, R.[Rosa], Fdez-Valdivia, J., Martinez-Baena, J.,
Information visibility using transmission methods,
PRL(31), No. 7, 1 May 2010, pp. 609-618.
Elsevier DOI 1004
Computational attention; Transmission; Paradigm; Visual efficiency; Important information; Advertising BibRef

Hirai, K.[Keita], Tumurtogoo, J.[Jambal], Kikuchi, A.[Ayano], Tsumura, N.[Norimichi], Nakaguchi, T.[Toshiya], Miyake, Y.[Yoichi],
Video Quality Assessment Using Spatio-Velocity Contrast Sensitivity Function,
IEICE(E93-D), No. 5, May 2010, pp. 1253-1262.
WWW Link. 1006
BibRef

Garaj, V., Hunaiti, Z., Balachandran, W.,
Using Remote Vision: The Effects of Video Image Frame Rate on Visual Object Recognition Performance,
SMC-A(40), No. 4, July 2010, pp. 698-707.
IEEE DOI 1007
BibRef

You, J.Y.[Jun-Yong], Reiter, U.[Ulrich], Hannuksela, M.M.[Miska M.], Gabbouj, M.[Moncef], Perkis, A.[Andrew],
Perceptual-based quality assessment for audio-visual services: A survey,
SP:IC(25), No. 7, August 2010, pp. 482-501.
Elsevier DOI 1008
Survey, Video Quality. Objective quality metric; Subjective quality assessment; HVS; Psychophysical approach; Engineering approach; Perception; Alignment; PEAQ; Semantic importance BibRef

You, J.Y.[Jun-Yong], Perkis, A., Gabbouj, M.,
Improving image quality assessment with modeling visual attention,
EUVIP10(177-182).
IEEE DOI 1110
BibRef

Hemami, S.S.[Sheila S.], Reibman, A.R.[Amy R.],
No-reference image and video quality estimation: Applications and human-motivated design,
SP:IC(25), No. 7, August 2010, pp. 469-481.
Elsevier DOI 1008
No-reference; Video quality; Quality metrics; Quality estimator; Applications of quality metrics; Blind quality assessment BibRef

Reibman, A.R., Vaishampayan, V.,
Low-Complexity Quality Monitoring of MPEG-2 Video in a Network,
ICIP03(III: 261-264).
IEEE DOI 0312
BibRef

Apostolopoulos, J.G., Reibman, A.R.,
The Challenge of Estimating Video Quality in Video Communication Applications,
SPMag(28), No. 2, 2011, pp. 160-158.
IEEE DOI 1203
[In the Spotlight] BibRef

Le Meur, O., Ninassi, A., Le Callet, P.[Patrick], Barba, D.[Dominique],
Do video coding impairments disturb the visual attention deployment?,
SP:IC(25), No. 8, September 2010, pp. 597-609.
Elsevier DOI 1003
BibRef
Earlier: A2, A1, A3, A4:
Does where you Gaze on an Image Affect your Perception of Quality? Applying Visual Attention to Image Quality Metric,
ICIP07(II: 169-172).
IEEE DOI 0709
Visual attention; Visual quality; Saliency; Video coding; H.264/AVC BibRef

Ivanovici, M.[Mihai], Richard, N.[Noël], Fernandez-Maloigne, C.[Christine],
Towards Video Quality Metrics Based on Colour Fractal Geometry,
JIVP(2010), No. 2010, pp. xx-yy.
DOI Link 1011
BibRef

Ivanovici, M., Richard, N.,
Fractal Dimension of Color Fractal Images,
IP(20), No. 1, January 2011, pp. 227-235.
IEEE DOI 1101
BibRef

Ivanovici, M.,
Fractal Dimension of Color Fractal Images With Correlated Color Components,
IP(29), 2020, pp. 8069-8082.
IEEE DOI 2008
Image color analysis, Fractals, Correlation, Complexity theory, Color, Mathematical model, Histograms, Color fractal dimension, color fractal image generation BibRef

Xia, T.[Tian], Mei, T.[Tao], Hua, G.[Gang], Zhang, Y.D.[Yong-Dong], Hua, X.S.[Xian-Sheng],
Visual quality assessment for web videos,
JVCIR(21), No. 8, November 2010, pp. 826-837.
Elsevier DOI 1011
Visual quality assessment; Web video; Non-reference; Domain specific BibRef

Huang, Y.H., Ou, T.S., Su, P.Y., Chen, H.H.,
Perceptual Rate-Distortion Optimization Using Structural Similarity Index as Quality Metric,
CirSysVideo(20), No. 11, November 2010, pp. 1614-1624.
IEEE DOI 1011
BibRef

Yang, F.Z.[Fu-Zheng], Wan, S.A.[Shu-Ai], Xie, Q., Wu, H.R.,
No-Reference Quality Assessment for Networked Video via Primary Analysis of Bit Stream,
CirSysVideo(20), No. 11, November 2010, pp. 1544-1554.
IEEE DOI 1011
BibRef

Yang, F.Z.[Fu-Zheng], Wan, S.A.[Shu-Ai],
Spatial-temporal Video Quality Assessment Based On Two-level Temporal Pooling,
IJIG(11), No. 2, April 2011, pp. 235-249.
DOI Link 1107

See also Lagrange multiplier selection in wavelet-based scalable video coding for quality scalability. BibRef

Huang, S.C.,
An Advanced Motion Detection Algorithm With Video Quality Analysis for Video Surveillance Systems,
CirSysVideo(21), No. 1, January 2011, pp. 1-14.
IEEE DOI 1103
BibRef

Dosselmann, R.[Richard], Yang, X.D.[Xue Dong],
A comprehensive assessment of the structural similarity index,
SIViP(5), No. 1, March 2011, pp. 81-91.
WWW Link. 1103
BibRef
Earlier:
A Prototype No-Reference Video Quality System,
CRV07(411-417).
IEEE DOI 0705
BibRef

Culibrk, D., Mirkovic, M., Zlokolica, V., Pokric, M., Crnojevic, V., Kukolj, D.,
Salient Motion Features for Video Quality Assessment,
IP(20), No. 4, April 2011, pp. 948-958.
IEEE DOI 1103
BibRef

Voran, S.[Stephen], Catellier, A.[Andrew],
Gradient Ascent Subjective Multimedia Quality Testing,
JIVP(2011), No. 2011, pp. xx-yy.
DOI Link 1103
BibRef

Garcia, M.N., Schleicher, R., Raake, A.,
Impairment-Factor-Based Audiovisual Quality Model for IPTV: Influence of Video Resolution, Degradation Type, and Content Type,
JIVP(2011), No. 2011, pp. xx-yy.
DOI Link 1104
BibRef

Wang, Z.[Zhou], Li, Q.A.[Qi-Ang],
Information Content Weighting for Perceptual Image Quality Assessment,
IP(20), No. 5, May 2011, pp. 1185-1198.
IEEE DOI 1104
BibRef
Earlier: A2, A1:
Video Quality Assessment by Incorporating a Motion Perception Model,
ICIP07(II: 173-176).
IEEE DOI 0709

See also Perceptual Image Coding Based on a Maximum of Minimal Structural Similarity Criterion. BibRef

Hiremath, B.[Basavaraj], Li, Q.A.[Qi-Ang], Wang, Z.[Zhou],
Quality-Aware Video,
ICIP07(III: 469-472).
IEEE DOI 0709
BibRef

Deshpande, S.[Sachin], Daly, S.[Scott],
Quality of Experience for Large Ultra-High-Resolution Tiled Displays with Synchronization Mismatch,
JIVP(2011), No. 2011, pp. xx-yy.
DOI Link 1104
BibRef

Liu, H.T.[Hao-Ting], Li, J.[Jie], Wang, Z.[Zheng], Cheng, J.[Jian], Lu, H.Q.[Han-Qing], Zhao, Y.[Yan],
Image Quality Feedback-based Adaptive Video Definition Improvement For The Space Manipulation Task,
IJIG(11), No. 2, April 2011, pp. 153-175.
DOI Link 1107
BibRef

Mu, M.[Mu], Mauthe, A.[Andreas], Haley, R.[Robert], Garcia, F.[Francisco],
Discrete quality assessment in IPTV content distribution networks,
SP:IC(26), No. 7, August 2011, pp. 339-357.
Elsevier DOI 1108
IPTV; Quality of experience; Quality assessment; Deep packet inspection BibRef

Lee, J.S.[Jong-Seok], de Simone, F., Ebrahimi, T.,
Subjective Quality Evaluation via Paired Comparison: Application to Scalable Video Coding,
MultMed(13), No. 5, 2011, pp. 882-893.
IEEE DOI 1110
BibRef

Lee, J.S.[Jong-Seok],
On Designing Paired Comparison Experiments for Subjective Multimedia Quality Assessment,
MultMed(16), No. 2, February 2014, pp. 564-571.
IEEE DOI 1404
least mean squares methods BibRef

Coverdale, P., Moller, S., Raake, A., Takahashi, A.,
Multimedia Quality Assessment Standards in ITU-T SG12,
SPMag(28), No. 1, 2011, pp. 91-97.
IEEE DOI 1112
BibRef

Porikli, F.M., Bovik, A.C., Plack, C., Al Regib, G.I., Farrell, J., Le Callet, P.[Patrick], Huynh-Thu, Q.[Quan], Moller, S., Winkler, S.,
Multimedia Quality Assessment,
SPMag(28), No. 1, 2011, pp. 164-177.
IEEE DOI 1112
[DSP Forum] BibRef

Park, J., Seshadrinathan, K., Lee, S., Bovik, A.C.,
Video Quality Pooling Adaptive to Perceptual Distortion Severity,
IP(22), No. 2, February 2013, pp. 610-620.
IEEE DOI 1302
BibRef

You, J.Y., Korhonen, J., Perkis, A., Ebrahimi, T.,
Balancing Attended and Global Stimuli in Perceived Video Quality Assessment,
MultMed(13), No. 6, 2011, pp. 1269-1285.
IEEE DOI 1112
BibRef

You, J.Y.[Jun-Yong], Ebrahimi, T., Perkis, A.,
Attention Driven Foveated Video Quality Assessment,
IP(23), No. 1, January 2014, pp. 200-213.
IEEE DOI 1402
image representation BibRef

Pinson, M.H., Ingram, W., Webster, A.,
Audiovisual Quality Components,
SPMag(28), No. 1, 2011, pp. 60-67.
IEEE DOI 1112
BibRef

Keimel, C., Rothbucher, M., Shen, H.[Hao], Diepold, K.,
Video is a Cube,
SPMag(28), No. 1, 2011, pp. 41-49.
IEEE DOI 1112
Quality of experience in multi-media. Consider the full 3-D data. BibRef

Zhao, Y., Yu, L., Chen, Z., Zhu, C.,
Video Quality Assessment Based on Measuring Perceptual Noise From Spatial and Temporal Perspectives,
CirSysVideo(21), No. 12, December 2011, pp. 1890-1902.
IEEE DOI 1112
BibRef

Liao, N.[Ning], Chen, Z.B.[Zhi-Bo],
A packet-layer video quality assessment model with spatiotemporal complexity estimation,
JIVP(2011), No. 1 2011, pp. xx-yy.
DOI Link 1203
BibRef

Lin, C., Chen, Z.B.[Zhi-Bo], Liao, N.[Ning],
Full-reference quality assessment for stereoscopic images based on binocular vision model,
VCIP16(1-4)
IEEE DOI 1701
Databases BibRef

Gong, H.F.[Hai-Feng], Zhu, S.C.[Song-Chun],
Intrackability: Characterizing Video Statistics and Pursuing Video Representations,
IJCV(97), No. 3, May 2012, pp. 255-275.
WWW Link. 1203
Measure video complexity to get better representation. (I.e. measure of how hard to track.) Relate to Shi-Tomasi texture and Harris-Stephens.
See also Combined Corner and Edge Detector, A.
See also integrated background model for video surveillance based on primal sketch and 3D scene geometry, An. BibRef

Scholler, S., Bosse, S., Treder, M.S., Blankertz, B., Curio, G., Muller, K.R., Wiegand, T.,
Toward a Direct Measure of Video Quality Perception Using EEG,
IP(21), No. 5, May 2012, pp. 2619-2629.
IEEE DOI 1204
BibRef

Xu, Q.Q., Huang, Q.M., Jiang, T., Yan, B., Lin, W., Yao, Y.,
HodgeRank on Random Graphs for Subjective Video Quality Assessment,
MultMed(14), No. 3, 2012, pp. 844-857.
IEEE DOI 1202
BibRef

Xu, Q.Q.[Qian-Qian], Xiong, J.C.[Jie-Chao], Huang, Q.M.[Qing-Ming], Yao, Y.[Yuan],
Online HodgeRank on Random Graphs for Crowdsourceable QoE Evaluation,
MultMed(16), No. 2, February 2014, pp. 373-386.
IEEE DOI 1404
Internet BibRef

Wang, Y.[Yue], Jiang, T.T.[Ting-Ting], Ma, S.W.[Si-Wei], Gao, W.[Wen],
Novel Spatio-Temporal Structural Information Based Video Quality Metric,
CirSysVideo(22), No. 7, July 2012, pp. 989-998.
IEEE DOI 1208
BibRef

Han, J.J.[Jing-Jing], Jiang, T.T.[Ting-Ting], Ma, S.W.[Si-Wei],
Stereoscopic video quality assessment model based on spatial-temporal structural information,
VCIP12(1-6).
IEEE DOI 1302
BibRef

Menkovski, V.[Vlado], Liotta, A.[Antonio],
Adaptive psychometric scaling for video quality assessment,
SP:IC(27), No. 8, September 2012, pp. 788-799.
Elsevier DOI 1209
Psychometric quality scaling; Maximum likelihood difference scaling; Adaptive MLDS; Video quality assessment BibRef

da Silva, W.B.[Wyllian Bezerra], Fonseca, K.V.O.[Keiko Verônica Ono], Pohl, A.D.P.[Alexandre De_Almeida Prado],
A Reduced-Reference Video Quality Assessment Method Based on the Activity-Difference of DCT Coefficients,
IEICE(E96-D), No. 3, March 2013, pp. 708-718.
WWW Link. 1303
BibRef

da Silva, W.B.[Wyllian Bezerra], Fonseca, K.V.O.[Keiko Verônica Ono], Pohl, A.D.P.[Alexandre De_Almeida Prado],
Objective No-Reference Video Quality Assessment Method Based on Spatio-Temporal Pixel Analysis,
IEICE(E98-D), No. 7, July 2015, pp. 1325-1332.
WWW Link. 1508
BibRef

Romani, E.[Eduardo], da Silva, W.B.[Wyllian Bezerra], Fonseca, K.V.O.[Keiko Verônica Ono], Culibrk, D.[Dubravko], Pohl, A.D.P.[Alexandre De_Almeida Prado],
Full-Reference SSIM Metric for Video Quality Assessment with Saliency-Based Features,
QoEM15(547-554).
Springer DOI 1511
BibRef

Zhang, F.[Fan], Lin, W.S.[Wei-Si], Chen, Z.B.[Zhi-Bo], Ngan, K.N.[King Ngi],
Additive Log-Logistic Model for Networked Video Quality Assessment,
IP(22), No. 4, April 2013, pp. 1536-1547.
IEEE DOI 1303
BibRef

Oran, D.[David],
Technical Perspective: Video Quality Assessment in the Age of Internet Video,
CACM(56), No. 3, March 2013, pp. 90.
DOI Link 1304
With video delivery, it appears that once again "the Internet changes everything." In this changed environment, what measures of quality are most relevant, and how are they obtained from consumers BibRef

Dobrian, F.[Florin], Awan, A.[Asad], Joseph, D.[Dilip], Ganjam, A.[Aditya], Zhan, J.[Jibin], Sekar, V.[Vyas], Stoica, I.[Ion], Zhang, H.[Hui],
Understanding the Impact of Video Quality on User Engagement,
CACM(56), No. 3, March 2013, pp. 91-99.
DOI Link 1304
As Internet-based videos become mainstream, user expectation for high quality is constantly increasing. In this context, it is crucial for content providers to understand how video quality affects user engagement BibRef

de Silva, V., Arachchi, H.K., Ekmekcioglu, E., Kondoz, A.,
Toward an Impairment Metric for Stereoscopic Video: A Full-Reference Video Quality Metric to Assess Compressed Stereoscopic Video,
IP(22), No. 9, 2013, pp. 3392-3404.
IEEE DOI 1308
data compression BibRef

Leszczuk, M.[Mikolaj], Janowski, L.[Lucjan], Romaniak, P.[Piotr], Papir, Z.[Zdzislaw],
Assessing quality of experience for high definition video streaming under diverse packet loss patterns,
SP:IC(28), No. 8, 2013, pp. 903-916.
Elsevier DOI 1309
Objective evaluation techniques BibRef

Seyedebrahimi, M., Bailey, C., Peng, X.H.,
Model and Performance of a No-Reference Quality Assessment Metric for Video Streaming,
CirSysVideo(23), No. 12, 2013, pp. 2034-2043.
IEEE DOI 1312
Analytical models BibRef

Satgunam, P.N., Woods, R.L., Bronstad, P.M., Peli, E.,
Factors Affecting Enhanced Video Quality Preferences,
IP(22), No. 12, 2013, pp. 5146-5157.
IEEE DOI 1312
BibRef
And: Erratum: IP(23), No. 1, January 2014, pp. 479-479.
IEEE DOI 1402
Biomedical imaging data compression BibRef

Yeh, H.H.[Hsin-Ho], Yang, C.Y.[Chun-Yu], Lee, M.S.[Ming-Sui], Chen, C.S.[Chu-Song],
Video Aesthetic Quality Assessment by Temporal Integration of Photo- and Motion-Based Features,
MultMed(15), No. 8, December 2013, pp. 1944-1957.
IEEE DOI 1402
feature extraction BibRef

Sedano, I.[Inigo], Brunnstrom, K.[Kjell], Kihl, M.[Maria], Aurelius, A.[Andreas],
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video signal processing BibRef

Mantel, C., Bech, S., Korhonen, J., Forchhammer, S., Pedersen, J.M.,
Modeling the Subjective Quality of Highly Contrasted Videos Displayed on LCD With Local Backlight Dimming,
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image sequences BibRef

Mantel, C., Søgaard, J., Bech, S., Korhonen, J., Pedersen, J.M., Forchhammer, S.,
Modeling the Quality of Videos Displayed With Local Dimming Backlight at Different Peak White and Ambient Light Levels,
IP(25), No. 8, August 2016, pp. 3751-3761.
IEEE DOI 1608
Analysis of variance BibRef

Pinson, M.H., Janowski, L., Papir, Z.,
Video Quality Assessment: Subjective testing of entertainment scenes,
SPMag(32), No. 1, January 2015, pp. 101-114.
IEEE DOI 1502
video signal processing BibRef

Torkamani-Azar, F.[Farah], Imani, H.[Hassan], Fathollahian, H.[Hossein],
Video quality measurement based on 3-D Singular value decomposition,
JVCIR(27), No. 1, 2015, pp. 1-6.
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Image Quality assessment BibRef

Zhu, K.F.[Kong-Feng], Li, C., Asari, V.[Vijayan], Saupe, D.[Dietmar],
No-Reference Video Quality Assessment Based on Artifact Measurement and Statistical Analysis,
CirSysVideo(25), No. 4, April 2015, pp. 533-546.
IEEE DOI 1504
Discrete cosine transforms BibRef

Zhu, K.F.[Kong-Feng], Hirakawa, K.[Keigo], Asari, V.[Vijayan], Saupe, D.[Dietmar],
A no-reference video quality assessment based on Laplacian pyramids,
ICIP13(49-53)
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Databases BibRef

Narwaria, M.[Manish], da Silva, M.P.[Matthieu Perreira], Le Callet, P.[Patrick],
HDR-VQM: An objective quality measure for high dynamic range video,
SP:IC(35), No. 1, 2015, pp. 46-60.
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High dynamic range (HDR) video quality BibRef

Vigier, T., da Silva, M.P.[Matthieu Perreira], Le Callet, P.[Patrick],
Impact of visual angle on attention deployment and robustness of visual saliency models in videos: From SD to UHD,
ICIP16(689-693)
IEEE DOI 1610
Computational modeling BibRef

Choi, L.K.[Lark Kwon], Cormack, L.K.[Lawrence K.], Bovik, A.C.[Alan C.],
Motion silencing of flicker distortions on naturalistic videos,
SP:IC(39, Part B), No. 1, 2015, pp. 328-341.
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Motion silencing BibRef

Choi, L.K.[Lark Kwon], Bovik, A.C.[Alan C.],
Flicker sensitive motion tuned video quality assessment,
Southwest16(29-32)
IEEE DOI 1605
Band-pass filters BibRef

Hameed, A., Dai, R., Balas, B.,
A Decision-Tree-Based Perceptual Video Quality Prediction Model and Its Application in FEC for Wireless Multimedia Communications,
MultMed(18), No. 4, April 2016, pp. 764-774.
IEEE DOI 1604
Forward error correction BibRef

Tuohy, S.[Shane], Winterlich, A.[Anthony], McGinley, B.[Brian], Glavin, M.[Martin], Jones, E.[Edward], Denny, P.[Patrick], Kilmartin, L.[Liam],
Evaluating the influence of packet loss on visual quality of perception for high bandwidth automotive networks,
SP:IC(43), No. 1, 2016, pp. 15-27.
Elsevier DOI 1604
Packet loss BibRef

Chen, Z., Liao, N., Gu, X., Wu, F., Shi, G.,
Hybrid Distortion Ranking Tuned Bitstream-Layer Video Quality Assessment,
CirSysVideo(26), No. 6, June 2016, pp. 1029-1043.
IEEE DOI 1606
Degradation BibRef

Li, X., Guo, Q., Lu, X.,
Spatiotemporal Statistics for Video Quality Assessment,
IP(25), No. 7, July 2016, pp. 3329-3342.
IEEE DOI 1606
Distortion BibRef

Scott, M.J., Guntuku, S.C., Lin, W., Ghinea, G.,
Do Personality and Culture Influence Perceived Video Quality and Enjoyment?,
MultMed(18), No. 9, September 2016, pp. 1796-1807.
IEEE DOI 1609
cultural aspects BibRef

Jang, S., Lee, J.S.,
On Evaluating Perceptual Quality of Online User-Generated Videos,
MultMed(18), No. 9, September 2016, pp. 1808-1818.
IEEE DOI 1609
Internet BibRef

Mercer Moss, F.[Felix], Wang, K., Zhang, F.[Fan], Baddeley, R.[Roland], Bull, D.R.[David R.],
On the Optimal Presentation Duration for Subjective Video Quality Assessment,
CirSysVideo(26), No. 11, November 2016, pp. 1977-1987.
IEEE DOI 1609
Context BibRef

Mercer Moss, F.[Felix], Yeh, C.T.[Chun-Ting], Zhang, F.[Fan], Baddeley, R.[Roland], Bull, D.R.[David R.],
Support for reduced presentation durations in subjective video quality assessment,
SP:IC(48), No. 1, 2016, pp. 38-49.
Elsevier DOI 1609
Subjective testing BibRef

Silva, A.F., Farias, M.C.Q.[Mylène C.Q.], Redi, J.A.,
Perceptual Annoyance Models for Videos With Combinations of Spatial and Temporal Artifacts,
MultMed(18), No. 12, December 2016, pp. 2446-2456.
IEEE DOI 1612
Codecs BibRef

Farias, M.C.Q., Mitra, S.K.,
No-Reference Video Quality Metric Based on Artifact Measurements,
ICIP05(III: 141-144).
IEEE DOI 0512
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Podder, P.K.[Pallab Kanti], Paul, M.[Manoranjan], Murshed, M.[Manzur],
QMET: A new quality assessment metric for no-reference video coding by using human eye traversal,
ICVNZ16(1-6)
IEEE DOI 1701
Correlation BibRef

Guo, J.F.[Jie-Feng], Hu, G.[Gong], Xu, W.J.[Wei-Jian], Huang, L.F.[Lian-Fen],
Hierarchical content importance-based video quality assessment for HEVC encoded videos transmitted over LTE networks,
JVCIR(43), No. 1, 2017, pp. 50-60.
Elsevier DOI 1702
Content type BibRef

Zhang, W., Liu, H.,
Study of Saliency in Objective Video Quality Assessment,
IP(26), No. 3, March 2017, pp. 1275-1288.
IEEE DOI 1703
distortion BibRef

Song, J., Yang, F., Zhou, Y., Gao, S.,
Parametric Planning Model for Video Quality Evaluation of IPTV Services Combining Channel and Video Characteristics,
MultMed(19), No. 5, May 2017, pp. 1015-1029.
IEEE DOI 1704
Distortion BibRef

Vega, M.T., Mocanu, D.C., Famaey, J., Stavrou, S., Liotta, A.,
Deep Learning for Quality Assessment in Live Video Streaming,
SPLetters(24), No. 6, June 2017, pp. 736-740.
IEEE DOI 1705
unsupervised learning, video signal processing, video streaming, FR benchmark, LIMP Video Quality Database, extensive packet loss impaired video set, inexpensive no-reference measurements, offline deep unsupervised learning processes, online analysis, quality assessment methods, real-time analysis, real-time assessment, video assessment method, video content providers, video quality metric, Feature extraction, Machine learning, Measurement, Quality assessment, Real-time systems, Streaming media, Video recording, Deep learning (DL), multimedia video services, unsupervised learning (UL), video, quality, assessment BibRef

Peng, P.[Peng], Liao, D.P.[Dan-Ping], Li, Z.N.[Ze-Nian],
An efficient temporal distortion measure of videos based on spacetime texture,
PR(70), No. 1, 2017, pp. 1-11.
Elsevier DOI 1706
Video, quality, assessment BibRef

Wang, H.Q.[Hai-Qiang], Katsavounidis, I.[Ioannis], Zhou, J.T.[Jian-Tong], Park, J.[Jeonghoon], Lei, S.[Shawmin], Zhou, X.[Xin], Pun, M.O.[Man-On], Jin, X.[Xin], Wang, R.G.[Rong-Gang], Wang, X.[Xu], Zhang, Y.[Yun], Huang, J.W.[Ji-Wu], Kwong, S.[Sam], Kuo, C.C.J.[C.C. Jay],
VideoSet: A large-scale compressed video quality dataset based on JND measurement,
JVCIR(46), No. 1, 2017, pp. 292-302.
Elsevier DOI 1706
Human visual system (HVS) BibRef

Al-Naji, A.[Ali], Lee, S.H.[Sang-Heon], Chahl, J.[Javaan],
Quality index evaluation of videos based on fuzzy interface system,
IET-IPR(11), No. 5, April 2017, pp. 292-300.
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Sun, Y., Lu, A., Yu, L.,
Weighted-to-Spherically-Uniform Quality Evaluation for Omnidirectional Video,
SPLetters(24), No. 9, September 2017, pp. 1408-1412.
IEEE DOI 1708
Distortion, Distortion measurement, Extraterrestrial measurements, Measurement uncertainty, Weight measurement, Objective quality evaluation, omnidirectional video, projection format BibRef

Sun, Y., Yu, L.,
Coding optimization based on weighted-to-spherically-uniform quality metric for 360 video,
VCIP17(1-4)
IEEE DOI 1804
distortion, quantisation (signal), video coding, CMP, CTU level, CTU position, ERP, WS-PSNR weights, adaptive quantization method, weighted quality BibRef

Hu, S., Jin, L., Wang, H., Zhang, Y., Kwong, S., Kuo, C.C.J.,
Objective Video Quality Assessment Based on Perceptually Weighted Mean Squared Error,
CirSysVideo(27), No. 9, September 2017, pp. 1844-1855.
IEEE DOI 1709
Distortion, Distortion measurement, Quality assessment, Sensitivity, Video recording, Visualization, Human visual system (HVS), BibRef

Bosse, S., Maniry, D., Müller, K.R., Wiegand, T., Samek, W.,
Deep Neural Networks for No-Reference and Full-Reference Image Quality Assessment,
IP(27), No. 1, January 2018, pp. 206-219.
IEEE DOI 1712
feature extraction, image colour analysis, learning (artificial intelligence), neural nets, regression BibRef

Ndjiki-Nya, P.[Patrick], Barrado, M.[Mikel], Wiegand, T.[Thomas],
Efficient Full-Reference Assessment of Image and Video Quality,
ICIP07(II: 125-128).
IEEE DOI 0709
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Zou, W.J.[Wen-Jie], Yang, F.Z.[Fu-Zheng], Wan, S.[Shuai],
Perceptual video quality metric for compression artefacts: from two-dimensional to omnidirectional,
IET-IPR(12), No. 3, March 2018, pp. 374-381.
DOI Link 1802
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Hatchett, J.[Jonathan], Debattista, K.[Kurt], Mukherjee, R.[Ratnajit], Bashford-Rogers, T.[Thomas], Chalmers, A.[Alan],
An evaluation of power transfer functions for HDR video compression,
VC(34), No. 2, February 2018, pp. 167-176.
Springer DOI 1802
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Freitas, P.G.[Pedro Garcia], Akamine, W.Y.L.[Welington Y.L.], Farias, M.C.Q.[Mylène C.Q.],
Using multiple spatio-temporal features to estimate video quality,
SP:IC(64), 2018, pp. 1-10.
Elsevier DOI 1804
Video quality assessment, Texture operator, Spatio-temporal texture analysis, Machine learning, Random forest regression BibRef

Akamine, W.Y.L.[Welington Y.L.], Freitas, P.G.[Pedro Garcia], Farias, M.C.Q.[Mylène C.Q.],
A framework for computationally efficient video quality assessment,
SP:IC(70), 2019, pp. 57-67.
Elsevier DOI 1812
Video quality assessment methods, Spatial resolution, Runtime performance BibRef

Choi, L.K.[Lark Kwon], Bovik, A.C.[Alan Conrad],
Video quality assessment accounting for temporal visual masking of local flicker,
SP:IC(67), 2018, pp. 182-198.
Elsevier DOI 1808
Video quality assessment, Temporal visual masking, Motion silencing, Flicker visibility, Human visual system BibRef

Narwaria, M., Krasula, L., Le Callet, P.[Patrick],
Data Analysis in Multimedia Quality Assessment: Revisiting the Statistical Tests,
MultMed(20), No. 8, August 2018, pp. 2063-2072.
IEEE DOI 1808
data analysis, multimedia communication, statistical testing, data analysis, multimedia quality assessment, objective methods, statistical analysis BibRef

Ghadiyaram, D., Pan, J., Bovik, A.C., Moorthy, A.K., Panda, P., Yang, K.,
In-Capture Mobile Video Distortions: A Study of Subjective Behavior and Objective Algorithms,
CirSysVideo(28), No. 9, September 2018, pp. 2061-2077.
IEEE DOI 1809
Distortion, Databases, Cameras, Quality assessment, Video recording, Mobile communication, Mobile handsets, Mobile videos, smart-phone cameras BibRef

Zhou, Y.[Yu], Li, L.[Leida], Wang, S.Q.[Shi-Qi], Wu, J.J.[Jin-Jian], Zhang, Y.[Yun],
No-reference quality assessment of DIBR-synthesized videos by measuring temporal flickering,
JVCIR(55), 2018, pp. 30-39.
Elsevier DOI 1809
Video quality evaluation, View synthesis, DIBR, Flickering, Singular value decomposition BibRef

Zhang, Y.[Yun], Zhang, H.[Huan], Yu, M.[Mei], Kwong, S.[Sam], Ho, Y.S.[Yo-Sung],
Sparse Representation-Based Video Quality Assessment for Synthesized 3D Videos,
IP(29), No. 1, 2020, pp. 509-524.
IEEE DOI 1910
data compression, distortion, image representation, rendering (computer graphics), video signal processing, temporal layer BibRef

Sinno, Z.[Zeina], Bovik, A.C.[Alan C.],
Large-Scale Study of Perceptual Video Quality,
IP(28), No. 2, February 2019, pp. 612-627.
IEEE DOI 1811
BibRef
Earlier:
Large Scale Subjective Video Quality Study,
ICIP18(276-280)
IEEE DOI 1809
cameras, data compression, image capture, video coding, video databases, video recording, video signal processing, multimedia. Distortion, Browsers, Training, Testing, Video Quality Assessment, Subjective Study, Crowdsourcing BibRef

Sinno, Z., Moorthy, A.K., de Cock, J., Li, Z., Bovik, A.C.,
Quality Measurement of Images on Mobile Streaming Interfaces Deployed at Scale,
IP(29), 2020, pp. 2536-2551.
IEEE DOI 2001
Streaming media, Databases, Distortion, Visualization, Image coding, Transform coding, Image quality assessment (IQA), mobile streaming BibRef

Singh, R.[Ranjit], Aggarwal, N.[Naveen],
A distortion-agnostic video quality metric based on multi-scale spatio-temporal structural information,
SP:IC(74), 2019, pp. 299-308.
Elsevier DOI 1904
Video quality assessment (VQA), No-reference (NR), Local binary patterns (LBP), Three orthogonal planes (TOP), Video quality dataset BibRef

Aldahdooh, A.[Ahmed], Masala, E.[Enrico], van Wallendael, G.[Glenn], Lambert, P.[Peter], Barkowsky, M.[Marcus],
Improving relevant subjective testing for validation: Comparing machine learning algorithms for finding similarities in VQA datasets using objective measures,
SP:IC(74), 2019, pp. 32-41.
Elsevier DOI 1904
Subjective testing, Subset selection, Statistical analysis, Video quality assessment, Clustering BibRef

Shang, X., Liang, J., Wang, G., Zhao, H., Wu, C., Lin, C.,
Color-Sensitivity-Based Combined PSNR for Objective Video Quality Assessment,
CirSysVideo(29), No. 5, May 2019, pp. 1239-1250.
IEEE DOI 1905
Sensitivity, Color, Encoding, Quality assessment, Visualization, Video recording, Video quality assessment, color sensitivity, PSNR, visual sensitivity BibRef

Aldahdooh, A., Masala, E., Janssens, O., van Wallendael, G., Barkowsky, M., Le Callet, P.[Patrick],
Improved Performance Measures for Video Quality Assessment Algorithms Using Training and Validation Sets,
MultMed(21), No. 8, August 2019, pp. 2026-2041.
IEEE DOI 1908
image sequences, learning (artificial intelligence), set theory, video signal processing, performance measures, content features BibRef

Bampis, C.G., Li, Z., Bovik, A.C.,
Spatiotemporal Feature Integration and Model Fusion for Full Reference Video Quality Assessment,
CirSysVideo(29), No. 8, August 2019, pp. 2256-2270.
IEEE DOI 1908
Streaming media, Quality assessment, Video recording, Feature extraction, Distortion measurement, VMAF BibRef

Zhang, Y., Gao, X., He, L., Lu, W., He, R.,
Blind Video Quality Assessment With Weakly Supervised Learning and Resampling Strategy,
CirSysVideo(29), No. 8, August 2019, pp. 2244-2255.
IEEE DOI 1908
Measurement, Feature extraction, Quality assessment, Spatiotemporal phenomena, Streaming media, Video recording, resampling BibRef

Heng, W., Jiang, T., Gao, W.,
How to Assess the Quality of Compressed Surveillance Videos Using Face Recognition,
CirSysVideo(29), No. 8, August 2019, pp. 2229-2243.
IEEE DOI 1908
Face, Surveillance, Task analysis, Face recognition, Feature extraction, Quality assessment, Video recording, face recognition BibRef

Papadopoulos, M.A.[Miltiadis Alexios], Katsenou, A.V.[Angeliki V.], Agrafiotis, D.[Dimitris], Bull, D.R.[David R.],
A multi-metric approach for block-level video quality assessment,
SP:IC(78), 2019, pp. 152-158.
Elsevier DOI 1909
Video quality assessment, Content features, Fusion of metrics, Block-level, RDO BibRef

Vranješ, M.[Mario], Bajcinovci, V.[Viliams], Grbic, R.[Ratko], Vajak, D.[Denis],
No-reference artifacts measurements based video quality metric,
SP:IC(78), 2019, pp. 345-358.
Elsevier DOI 1909
AMB-VQM, Video quality assessment, No-reference, Video artifacts, Video quality database BibRef

Athar, S., Costa, T., Zeng, K., Wang, Z.,
Perceptual Quality Assessment of UHD-HDR-WCG Videos,
ICIP19(1740-1744)
IEEE DOI 1910
video quality assessment, high dynamic range, wide color gamut, ultra high definition, 4K, subjective testing, objective analysis BibRef

Oh, S.R., Jeong, S., Heo, P., Kim, D., Kim, H.Y., Park, H.,
A New No-Reference Method for Judder Artifact Assessment,
CirSysVideo(29), No. 10, October 2019, pp. 2888-2898.
IEEE DOI 1910
image motion analysis, image sequences, motion compensation, regression analysis, video signal processing, visual perception, subjective assessment BibRef

Korhonen, J.,
Two-Level Approach for No-Reference Consumer Video Quality Assessment,
IP(28), No. 12, December 2019, pp. 5923-5938.
IEEE DOI 1909
Video recording, Quality assessment, Streaming media, Feature extraction, Distortion, Image coding, Databases, quality management BibRef

You, J., Korhonen, J.,
Deep Neural Networks for No-Reference Video Quality Assessment,
ICIP19(2349-2353)
IEEE DOI 1910
3D-CNN, deep learning, LSTM, video quality assessment BibRef

Mustafa, S.[Safi], Hameed, A.[Abdul],
Perceptual quality assessment of video using machine learning algorithm,
SIViP(13), No. 8, November 2019, pp. 1495-1502.
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Varga, D.[Domonkos], Szirányi, T.[Tamás],
No-reference video quality assessment via pretrained CNN and LSTM networks,
SIViP(13), No. 8, November 2019, pp. 1569-1576.
WWW Link. 1911
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Varga, D.[Domonkos],
Composition-preserving deep approach to full-reference image quality assessment,
SIViP(14), No. 6, September 2020, pp. 1265-1272.
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Yuan, Y.[Ying], Wang, C.[Cong],
IPTV video quality assessment model based on neural network,
JVCIR(64), 2019, pp. 102629.
Elsevier DOI 1911
BP neural network, IPTV video, Quality assessment, Clustering analysis BibRef

Wu, J., Liu, Y., Dong, W., Shi, G., Lin, W.,
Quality Assessment for Video With Degradation Along Salient Trajectories,
MultMed(21), No. 11, November 2019, pp. 2738-2749.
IEEE DOI 1911
Trajectory, Degradation, Motion measurement, Distortion measurement, Optical distortion, Distortion, spatial-temporal quality degradation BibRef

Kulupana, G., Talagala, D.S., Arachchi, H.K., Fernando, A.,
End User Video Quality Prediction and Coding Parameters Selection at the Encoder for Robust HEVC Video Transmission,
CirSysVideo(29), No. 11, November 2019, pp. 3367-3381.
IEEE DOI 1911
Distortion, Encoding, Decoding, Video recording, Quality assessment, Video coding, Prediction algorithms, HEVC, error concealment BibRef

Xu, M., Li, C., Chen, Z., Wang, Z., Guan, Z.,
Assessing Visual Quality of Omnidirectional Videos,
CirSysVideo(29), No. 12, December 2019, pp. 3516-3530.
IEEE DOI 1912
Videos, Measurement, Visualization, viewing direction Video coding, Databases, Distortion, Omnidirectional video coding, BibRef

Rohil, M.K.[Mukesh Kumar], Gupta, N.[Neetika], Yadav, P.[Prakash],
An improved model for no-reference image quality assessment and a no-reference video quality assessment model based on frame analysis,
SIViP(14), No. 1, February 2020, pp. 205-213.
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Liu, L.X.[Li-Xiong], Wang, T.S.[Tian-Shu], Huang, H.[Hua], Bovik, A.C.[Alan Conrad],
Video quality assessment using space-time slice mappings,
SP:IC(82), 2020, pp. 115749.
Elsevier DOI 2001
Video quality assessment, Image quality assessment, Spatial temporal slice, Space-time stability, Learning based pooling BibRef

Zheng, Q.[Qi], Tu, Z.Z.[Zheng-Zhong], Hao, Z.J.[Zhi-Jian], Zeng, X.Y.[Xiao-Yang], Bovik, A.C.[Alan C.], Fan, Y.[Yibo],
Blind Video Quality Assessment via Space-Time Slice Statistics,
ICIP22(451-455)
IEEE DOI 2211
Codes, Statistical analysis, Databases, User-generated content, Predictive models, Feature extraction, Distortion, user-generated content BibRef

Ebenezer, J.P.[Joshua Peter], Shang, Z.X.[Zai-Xi], Wu, Y.J.[Yong-Jun], Wei, H.[Hai], Sethuraman, S.[Sriram], Bovik, A.C.[Alan C.],
ChipQA: No-Reference Video Quality Prediction via Space-Time Chips,
IP(30), 2021, pp. 8059-8074.
IEEE DOI 2109
Quality assessment, Video recording, Prediction algorithms, Optical distortion, Visualization, Distortion, Databases, human visual system BibRef

Jin, Y.Z.[Yi-Ze], Patney, A.[Anjul], Webb, R.[Richard], Bovik, A.C.[Alan C.],
FOVQA: Blind Foveated Video Quality Assessment,
IP(31), 2022, pp. 4571-4584.
IEEE DOI 2207
Quality assessment, Predictive models, Video recording, Distortion, Solid modeling, Feature extraction, Visualization, virtual reality BibRef

Jin, Y.Z.[Yi-Ze], Goodall, T., Patney, A.[Anjul], Webb, R.[Richard], Bovik, A.C.[Alan C.],
A Foveated Video Quality Assessment Model Using Space-Variant Natural Scene Statistics,
ICIP21(1419-1423)
IEEE DOI 2201
Solid modeling, Stacking, Virtual reality, Streaming media, Video compression, Nonuniform sampling, Retina, foveation, virtual reality BibRef

Farid, M.S.[Muhammad Shahid], Lucenteforte, M.[Maurizio], Grangetto, M.[Marco],
No-reference quality metric for HEVC compression distortion estimation in depth maps,
SIViP(14), No. 1, February 2020, pp. 195-203.
Springer DOI 2001
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Cemiloglu, E.[Enes], Yilmaz, G.N.[Gokce Nur],
Blind video quality assessment via spatiotemporal statistical analysis of adaptive cube size 3D-DCT coefficients,
IET-IPR(14), No. 5, 17 April 2020, pp. 845-852.
DOI Link 2004
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Kazemi, M., Ghanbari, M., Shirmohammadi, S.,
The Performance of Quality Metrics in Assessing Error-Concealed Video Quality,
IP(29), 2020, pp. 5937-5952.
IEEE DOI 2005
Error/loss concealment, video quality assessment, image quality assessment BibRef

Bezerra da Silva, W.[Wyllian], Mikowski, A.[Alexandre], Casali, R.M.[Rafael Machado],
No-reference video quality assessment method based on spatio-temporal features using the ELM algorithm,
IET-IPR(14), No. 7, 29 May 2020, pp. 1316-1326.
DOI Link 2005
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Lin, L., Yu, S., Zhou, L., Chen, W., Zhao, T., Wang, Z.,
PEA265: Perceptual Assessment of Video Compression Artifacts,
CirSysVideo(30), No. 11, November 2020, pp. 3898-3910.
IEEE DOI 2011
Video coding, Databases, Encoding, Image color analysis, Visualization, Image coding, Hemorrhaging, Video coding, H265/HEVC BibRef

Ling, S., Li, J., Che, Z., Min, X., Zhai, G., Le Callet, P.,
Quality Assessment of Free-Viewpoint Videos by Quantifying the Elastic Changes of Multi-Scale Motion Trajectories,
IP(30), 2021, pp. 517-531.
IEEE DOI 2012
Distortion, Measurement, Trajectory, Videos, Quality assessment, Strain, Shape, Free-viewpoint video, free-viewpoint TV, video quality assessment BibRef

Wu, W., Li, Q., Chen, Z., Liu, S.,
Semantic Information Oriented No-Reference Video Quality Assessment,
SPLetters(28), 2021, pp. 204-208.
IEEE DOI 2102
Feature extraction, Semantics, Distortion, Quality assessment, Data mining, Video recording, Degradation, low-level features BibRef

Yang, J.C.[Jia-Chen], Liu, T.L.[Tian-Lin], Jiang, B.[Bin], Lu, W.[Wen], Meng, Q.G.[Qing-Gang],
Panoramic Video Quality Assessment Based on Non-Local Spherical CNN,
MultMed(23), 2021, pp. 797-809.
IEEE DOI 2102
convolutional neural nets, stereo image processing, video retrieval, video signal processing, virtual reality, spatiotemporal information BibRef

Li, D.Q.[Ding-Quan], Jiang, T.T.[Ting-Ting], Jiang, M.[Ming],
Unified Quality Assessment of in-the-Wild Videos with Mixed Datasets Training,
IJCV(129), No. 4, April 2021, pp. 1238-1257.
Springer DOI 2104
BibRef

Qian, L., Pan, T., Zheng, Y., Zhang, J., Li, M., Yu, B., Wang, B.,
No-Reference Nonuniform Distorted Video Quality Assessment Based on Deep Multiple Instance Learning,
MultMedMag(28), No. 1, January 2021, pp. 28-37.
IEEE DOI 2104
Feature extraction, Quality assessment, Distortion, Reliability, Video recording, Training, No reference, Video quality assessment, Multiple instance learning BibRef

Tu, Z.Z.[Zheng-Zhong], Wang, Y.L.[Yi-Lin], Birkbeck, N.[Neil], Adsumilli, B.[Balu], Bovik, A.C.[Alan C.],
UGC-VQA: Benchmarking Blind Video Quality Assessment for User Generated Content,
IP(30), 2021, pp. 4449-4464.
IEEE DOI 2104
Databases, Quality assessment, Video recording, Streaming media, Distortion, Image coding, Feature extraction, user-generated content BibRef

Yu, X.X.[Xiang-Xu], Tu, Z.Z.[Zheng-Zhong], Ying, Z.Q.[Zhen-Qiang], Bovik, A.C.[Alan C.], Birkbeck, N.[Neil], Wang, Y.L.[Yi-Lin], Adsumilli, B.[Balu],
Subjective Quality Assessment of User-Generated Content Gaming Videos,
VAQuality22(74-83)
IEEE DOI 2202
Industries, Analytical models, Databases, Conferences, User-generated content, Games BibRef

Saha, A.[Avinab], Chen, Y.C.[Yu-Chih], Davis, C.[Chase], Qiu, B.[Bo], Wang, X.M.[Xiao-Ming], Gowda, R.[Rahul], Katsavounidis, I.[Ioannis], Bovik, A.C.[Alan C.],
Study of Subjective and Objective Quality Assessment of Mobile Cloud Gaming Videos,
IP(32), 2023, pp. 3295-3310.
IEEE DOI 2307
Videos, Cloud gaming, Databases, Quality assessment, Data models, Video games, Industries, Mobile cloud gaming, cloud gaming video quality database BibRef

Tu, Z.Z.[Zheng-Zhong], Chen, C.J., Chen, L.H., Birkbeck, N.[Neil], Adsumilli, B.[Balu], Bovik, A.C.[Alan C.],
A Comparative Evaluation Of Temporal Pooling Methods For Blind Video Quality Assessment,
ICIP20(141-145)
IEEE DOI 2011
Video recording, Quality assessment, Hysteresis, Streaming media, Predictive models, Databases, Harmonic analysis, temporal visual masking BibRef

Oppong Bediako, D.[Daniel], Mou, X.Q.[Xuan-Qin],
Joint model of gradient magnitude and Gabor features via Spatio-Temporal slice,
JVCIR(79), 2021, pp. 103204.
Elsevier DOI 2109
Full-reference (FR) video quality assessment, Gradient magnitude, Gabor filter BibRef

Madhusudana, P.C.[Pavan C.], Birkbeck, N.[Neil], Wang, Y.L.[Yi-Lin], Adsumilli, B.[Balu], Bovik, A.C.[Alan C.],
ST-GREED: Space-Time Generalized Entropic Differences for Frame Rate Dependent Video Quality Prediction,
IP(30), 2021, pp. 7446-7457.
IEEE DOI 2109
Video recording, Quality assessment, Streaming media, Databases, Band-pass filters, Predictive models, Distortion, High frame rate, generalized Gaussian distribution BibRef

Yu, X.X.[Xiang-Xu], Birkbeck, N.[Neil], Wang, Y.L.[Yi-Lin], Bampis, C.G.[Christos G.], Adsumilli, B.[Balu], Bovik, A.C.[Alan C.],
Predicting the Quality of Compressed Videos With Pre-Existing Distortions,
IP(30), 2021, pp. 7511-7526.
IEEE DOI 2109
Videos, Predictive models, Image coding, Databases, Nonlinear distortion, Quality assessment, Computational modeling, user-generated-content BibRef

Sun, T.F.[Tong-Feng], Ding, S.F.[Shi-Fei], Chen, W.[Wei],
Blind video quality assessment based on multilevel video perception,
SP:IC(99), 2021, pp. 116485.
Elsevier DOI 2111
Blind video quality assessment, Natural video statistics, Motion features, Feature fusion, Video enhancement BibRef

Kancharla, P.[Parimala], Channappayya, S.S.[Sumohana S.],
Completely Blind Quality Assessment of User Generated Video Content,
IP(31), 2022, pp. 263-274.
IEEE DOI 2112
Feature extraction, Quality assessment, Computational modeling, Video recording, Prediction algorithms, Predictive models, video quality assessment (VQA) BibRef

Chen, P.F.[Peng-Fei], Li, L.D.[Lei-Da], Wu, J.J.[Jin-Jian], Dong, W.S.[Wei-Sheng], Shi, G.M.[Guang-Ming],
Contrastive Self-Supervised Pre-Training for Video Quality Assessment,
IP(31), 2022, pp. 458-471.
IEEE DOI 2112
Task analysis, Distortion, Predictive models, Quality assessment, Manuals, Data models, Streaming media, Video quality assessment, distortion augmentation BibRef

Gao, P.[Pan], Zhang, P.W.[Peng-Wei], Smolic, A.[Aljosa],
Quality Assessment for Omnidirectional Video: A Spatio-Temporal Distortion Modeling Approach,
MultMed(24), 2022, pp. 1-16.
IEEE DOI 2202
Measurement, Distortion, Quality assessment, Video recording, Visualization, Distortion measurement, spatio-temporal distortion BibRef

Luo, D.[Dengyan], Ye, M.[Mao], Li, S.[Shuai], Li, X.[Xue],
Coarse-to-Fine Spatio-Temporal Information Fusion for Compressed Video Quality Enhancement,
SPLetters(29), 2022, pp. 543-547.
IEEE DOI 2202
Convolution, Feature extraction, Training, Video recording, Quality assessment, Fuses, 3D convolution, deformable convolution, quality enhancement BibRef

Luo, D.[Dengyan], Ye, M.[Mao], Li, S.[Shuai], Zhu, C.[Ce], Li, X.[Xue],
Spatio-Temporal Detail Information Retrieval for Compressed Video Quality Enhancement,
MultMed(25), 2023, pp. 6808-6820.
IEEE DOI 2311
BibRef

Wang, Z.[Zeyang], Ye, M.[Mao], Li, S.[Shuai], Li, X.[Xue],
Multi-Frame Compressed Video Quality Enhancement by Spatio-Temporal Information Balance,
SPLetters(30), 2023, pp. 105-109.
IEEE DOI 2303
Feature extraction, Convolution, Signal processing algorithms, Encoding, Computational modeling, Image coding, spatio-temporal information BibRef

Wang, G.C.[Guang-Cheng], Wang, Z.Y.[Zhong-Yuan], Gu, K.[Ke], Jiang, K.[Kui], He, Z.[Zheng],
Reference-Free DIBR-Synthesized Video Quality Metric in Spatial and Temporal Domains,
CirSysVideo(32), No. 3, March 2022, pp. 1119-1132.
IEEE DOI 2203
Optical distortion, Distortion measurement, Quality assessment, Nonlinear distortion, Optical imaging, Integrated optics, spatial and temporal domains BibRef

Madhusudana, P.C.[Pavan C.], Birkbeck, N.[Neil], Wang, Y.L.[Yi-Lin], Adsumilli, B.[Balu], Bovik, A.C.[Alan C.],
Making Video Quality Assessment Models Sensitive to Frame Rate Distortions,
SPLetters(29), No. 2022, pp. 897-901.
IEEE DOI 2204
Streaming media, Predictive models, Entropy, Band-pass filters, Video recording, Quality assessment, Rate-distortion, feature fusion BibRef

Ebenezer, J.P.[Joshua P.], Shang, Z.X.[Zai-Xi], Wu, Y.J.[Yong-Jun], Wei, H.[Hai], Sethuraman, S.[Sriram], Bovik, A.C.[Alan C.],
Making Video Quality Assessment Models Robust to Bit Depth,
SPLetters(30), 2023, pp. 488-492.
IEEE DOI 2305
Databases, Feature extraction, Predictive models, Prediction algorithms, Nonlinear distortion, Dynamic range, video quality assessment BibRef

Otroshi-Shahreza, H.[Hatef], Amini, A.[Arash], Behroozi, H.[Hamid],
Feature-based no-reference video quality assessment using Extra Trees,
IET-IPR(16), No. 6, 2022, pp. 1531-1543.
DOI Link 2204
BibRef

Chen, B.L.[Bao-Liang], Zhu, L.Y.[Ling-Yu], Li, G.[Guo], Lu, F.B.[Fang-Bo], Fan, H.F.[Hong-Fei], Wang, S.Q.[Shi-Qi],
Learning Generalized Spatial-Temporal Deep Feature Representation for No-Reference Video Quality Assessment,
CirSysVideo(32), No. 4, April 2022, pp. 1903-1916.
IEEE DOI 2204
Feature extraction, Quality assessment, Training, Video recording, Image quality, Streaming media, Nonlinear distortion, temporal aggregation BibRef

Liu, Y.X.[Yong-Xu], Wu, J.J.[Jin-Jian], Li, L.[Leida], Dong, W.S.[Wei-Sheng], Zhang, J.P.[Jin-Peng], Shi, G.M.[Guang-Ming],
Spatiotemporal Representation Learning for Blind Video Quality Assessment,
CirSysVideo(32), No. 6, June 2022, pp. 3500-3513.
IEEE DOI 2206
Feature extraction, Spatiotemporal phenomena, Databases, Quality assessment, Video recording, Data models, Task analysis, weakly supervised learning BibRef

Liu, Y.X.[Yong-Xu], Wu, J.J.[Jin-Jian], Li, A.[Aobo], Li, L.[Leida], Dong, W.S.[Wei-Sheng], Shi, G.M.[Guang-Ming], Lin, W.S.[Wei-Si],
Video Quality Assessment With Serial Dependence Modeling,
MultMed(24), 2022, pp. 3754-3768.
IEEE DOI 2208
Degradation, Data mining, Video Quality Assessment, Serial Dependence, Long-Short Term Memory, Attention BibRef

Li, B.[Bowen], Zhang, W.X.[Wei-Xia], Tian, M.[Meng], Zhai, G.T.[Guang-Tao], Wang, X.[Xianpei],
Blindly Assess Quality of In-the-Wild Videos via Quality-Aware Pre-Training and Motion Perception,
CirSysVideo(32), No. 9, September 2022, pp. 5944-5958.
IEEE DOI 2209
Videos, Feature extraction, Databases, Distortion, Training, Quality assessment, Blind video quality assessment, in-the-wild videos BibRef

Dziembowski, A.[Adrian], Mieloch, D.[Dawid], Stankowski, J.[Jakub], Grzelka, A.[Adam],
IV-PSNR: The Objective Quality Metric for Immersive Video Applications,
CirSysVideo(32), No. 11, November 2022, pp. 7575-7591.
IEEE DOI 2211
Measurement, Image color analysis, Distortion, Cameras, Navigation, Image coding, Media, Image quality, immersive video, view synthesis BibRef

Vishwakarma, A.K.[Anish Kumar], Bhurchandi, K.M.[Kishor M.],
No-Reference Video Quality Assessment using novel hybrid features and two-stage hybrid regression for score level fusion,
JVCIR(89), 2022, pp. 103676.
Elsevier DOI 2212
Human visual system, No-reference video quality assessment, 3D steerable DWT, Perceptual features, User generated content, Support vector regression BibRef

Zheng, Q.[Qi], Tu, Z.Z.[Zheng-Zhong], Zeng, X.Y.[Xiao-Yang], Bovik, A.C.[Alan C.], Fan, Y.[Yibo],
A Completely Blind Video Quality Evaluator,
SPLetters(29), 2022, pp. 2228-2232.
IEEE DOI 2212
Video recording, Quality assessment, Feature extraction, Computational modeling, Streaming media, Distortion, linear model BibRef

Cao, L.[Lina], Guo, D.L.[Dong-Liang], Wang, Q.[Quan], Feng, L.[Li], Shi, C.[Chuanbao],
Video Quality Assessment of Danmaku-Based Video Saliency Regions,
SPLetters(29), 2022, pp. 2213-2217.
IEEE DOI 2212
Quality assessment, Visualization, Video recording, Sentiment analysis, Saliency detection, Image color analysis, Pearson correlation coefficient BibRef

Yang, L.[Li], Xu, M.[Mai], Li, S.X.[Sheng-Xi], Guo, Y.C.[Yi-Chen], Wang, Z.[Zulin],
Blind VQA on 360° Video via Progressively Learning From Pixels, Frames, and Video,
IP(32), 2023, pp. 128-143.
IEEE DOI 2301
Task analysis, Degradation, Quality assessment, Distortion, Visualization, Convolutional neural networks, Image coding, progressively learning BibRef

Li, Y.[Yang], Meng, S.B.[Sheng-Bin], Zhang, X.F.[Xin-Feng], Wang, M.[Meng], Wang, S.Q.[Shi-Qi], Wang, Y.[Yue], Ma, S.W.[Si-Wei],
User-Generated Video Quality Assessment: A Subjective and Objective Study,
MultMed(25), 2023, pp. 154-166.
IEEE DOI 2301
Quality assessment, Distortion, Video recording, Databases, Feature extraction, Convolutional neural networks, video quality assessment BibRef

Zhu, H.[Hanwei], Chen, B.[Baoliang], Zhu, L.[Lingyu], Wang, S.Q.[Shi-Qi],
Learning Spatiotemporal Interactions for User-Generated Video Quality Assessment,
CirSysVideo(33), No. 3, March 2023, pp. 1031-1042.
IEEE DOI 2303
Distortion, Transformers, Feature extraction, Spatiotemporal phenomena, Video recording, Quality assessment, vision transformer BibRef

Liu, Y.[Yongxu], Wu, J.J.[Jin-Jian], Li, L.[Leida], Dong, W.S.[Wei-Sheng], Shi, G.M.[Guang-Ming],
Quality Assessment of UGC Videos Based on Decomposition and Recomposition,
CirSysVideo(33), No. 3, March 2023, pp. 1043-1054.
IEEE DOI 2303
Dynamics, Videos, Degradation, Task analysis, Quality assessment, Streaming media, User-Generated Content, progressive aggregation BibRef

Cao, Y.Q.[Yu-Qin], Min, X.K.[Xiong-Kuo], Sun, W.[Wei], Zhai, G.T.[Guang-Tao],
Attention-Guided Neural Networks for Full-Reference and No-Reference Audio-Visual Quality Assessment,
IP(32), 2023, pp. 1882-1896.
IEEE DOI 2303
BibRef
Earlier:
Deep Neural Networks for Full-Reference and No-Reference Audio-Visual Quality Assessment,
ICIP21(1429-1433)
IEEE DOI 2201
Feature extraction, Visualization, Quality assessment, Measurement, Streaming media, Video recording, multimodal fusion. Deep learning, Databases, Fuses, Logic gates, Audio-visual quality assessment, multimodal fusion BibRef

Chen, Y.C.[Yu-Chih], Saha, A.[Avinab], Davis, C.[Chase], Qiu, B.[Bo], Wang, X.M.[Xiao-Ming], Gowda, R.[Rahul], Katsavounidis, I.[Ioannis], Bovik, A.C.[Alan C.],
GAMIVAL: Video Quality Prediction on Mobile Cloud Gaming Content,
SPLetters(30), 2023, pp. 324-328.
IEEE DOI 2304
Streaming media, Feature extraction, Computational modeling, Quality assessment, Video recording, Predictive models, temporal statistics BibRef

Fang, Y.M.[Yu-Ming], Li, Z.Q.[Zhao-Qian], Yan, J.[Jiebin], Sui, X.J.[Xiang-Jie], Liu, H.T.[Han-Tao],
Study of Spatio-Temporal Modeling in Video Quality Assessment,
IP(32), 2023, pp. 2693-2702.
IEEE DOI 2305
Feature extraction, Streaming media, Quality assessment, Video recording, Training, Solid modeling, recurrent neural network BibRef

Chen, P.F.[Peng-Fei], Li, L.[Leida], Li, H.L.[Hao-Liang], Wu, J.J.[Jin-Jian], Dong, W.S.[Wei-Sheng], Shi, G.M.[Guang-Ming],
Dynamic Expert-Knowledge Ensemble for Generalizable Video Quality Assessment,
CirSysVideo(33), No. 6, June 2023, pp. 2577-2589.
IEEE DOI 2306
Quality assessment, Training, Streaming media, Video recording, Feature extraction, Distortion, Data models, ensemble learning BibRef

Lin, L.Q.[Li-Qun], Zheng, Y.[Yang], Chen, W.L.[Wei-Ling], Lan, C.D.[Cheng-Dong], Zhao, T.S.[Tie-Song],
Saliency-Aware Spatio-Temporal Artifact Detection for Compressed Video Quality Assessment,
SPLetters(30), 2023, pp. 693-697.
IEEE DOI 2307
Visualization, Quality assessment, Video recording, Predictive models, Feature extraction, Image edge detection, compression artifact BibRef

Cao, Y.Q.[Yu-Qin], Min, X.K.[Xiong-Kuo], Sun, W.[Wei], Zhai, G.T.[Guang-Tao],
Subjective and Objective Audio-Visual Quality Assessment for User Generated Content,
IP(32), 2023, pp. 3847-3861.
IEEE DOI 2307
Databases, Quality assessment, Benchmark testing, Visualization, Visual databases, Streaming media, Feature extraction, multimodal fusion BibRef

Cao, Y.Q.[Yu-Qin], Min, X.K.[Xiong-Kuo], Sun, W.[Wei], Zhang, X.P.[Xiao-Ping], Zhai, G.T.[Guang-Tao],
Audio-Visual Quality Assessment for User Generated Content: Database and Method,
ICIP23(1495-1499)
IEEE DOI 2312
BibRef

Zhao, K.[Kai], Yuan, K.[Kun], Sun, M.[Ming], Wen, X.[Xing],
Zoom-VQA: Patches, Frames and Clips Integration for Video Quality Assessment,
NTIRE23(1302-1310)
IEEE DOI 2309
BibRef

Zhang, Z.C.[Zi-Cheng], Wu, W.[Wei], Sun, W.[Wei], Tu, D.Y.[Dan-Yang], Lu, W.[Wei], Min, X.K.[Xiong-Kuo], Chen, Y.[Ying], Zhai, G.T.[Guang-Tao],
MD-VQA: Multi-Dimensional Quality Assessment for UGC Live Videos,
CVPR23(1746-1755)
IEEE DOI 2309
BibRef

Madhusudana, P.C.[Pavan C.], Birkbeck, N.[Neil], Wang, Y.[Yilin], Adsumilli, B.[Balu], Bovik, A.C.[Alan C.],
CONVIQT: Contrastive Video Quality Estimator,
IP(32), 2023, pp. 5138-5152.
IEEE DOI 2310
BibRef

Wu, H.N.[Hao-Ning], Chen, C.F.[Chao-Feng], Liao, L.[Liang], Hou, J.W.[Jing-Wen], Sun, W.X.[Wen-Xiu], Yan, Q.[Qiong], Lin, W.S.[Wei-Si],
DisCoVQA: Temporal Distortion-Content Transformers for Video Quality Assessment,
CirSysVideo(33), No. 9, September 2023, pp. 4840-4854.
IEEE DOI Code:
WWW Link. 2310
BibRef

Wu, H.N.[Hao-Ning], Chen, C.F.[Chao-Feng], Liao, L.[Liang], Hou, J.W.[Jing-Wen], Sun, W.X.[Wen-Xiu], Yan, Q.[Qiong], Gu, J.W.[Jin-Wei], Lin, W.S.[Wei-Si],
Neighbourhood Representative Sampling for Efficient End-to-End Video Quality Assessment,
PAMI(45), No. 12, December 2023, pp. 15185-15202.
IEEE DOI 2311
BibRef

Wu, H.N.[Hao-Ning], Chen, C.F.[Chao-Feng], Hou, J.W.[Jing-Wen], Liao, L.[Liang], Wang, A.[Annan], Sun, W.X.[Wen-Xiu], Yan, Q.[Qiong], Lin, W.S.[Wei-Si],
FAST-VQA: Efficient End-to-End Video Quality Assessment with Fragment Sampling,
ECCV22(VI:538-554).
Springer DOI 2211
BibRef

Guan, X.D.[Xiao-Di], Li, F.[Fan], Zhang, Y.F.[Yang-Fan], Cosman, P.C.[Pamela C],
End-to-End Blind Video Quality Assessment Based on Visual and Memory Attention Modeling,
MultMed(25), 2023, pp. 5206-5221.
IEEE DOI 2311
BibRef

Zhou, F.[Fei], Yuan, S.H.[Shu-Hong], Liang, Z.J.[Zhi-Jie], Duan, J.[Jiang], Qiu, G.P.[Guo-Ping],
A Dataset and Model for the Visual Quality Assessment of Inversely Tone-Mapped HDR Videos,
IP(33), 2024, pp. 366-381.
IEEE DOI 2401
BibRef

Venkataramanan, A.K.[Abhinau K.], Stejerean, C.[Cosmin], Katsavounidis, I.[Ioannis], Bovik, A.C.[Alan C.],
One Transform to Compute Them All: Efficient Fusion-Based Full-Reference Video Quality Assessment,
IP(33), 2024, pp. 509-524.
IEEE DOI 2401
Computational modeling, Streaming media, Quality assessment, Image coding, Solid modeling, Bit rate, Video recording, contrast sensitivity BibRef

Zheng, Q.[Qi], Tu, Z.Z.[Zheng-Zhong], Madhusudana, P.C.[Pavan C.], Zeng, X.Y.[Xiao-Yang], Bovik, A.C.[Alan C.], Fan, Y.[Yibo],
FAVER: Blind quality prediction of variable frame rate videos,
SP:IC(122), 2024, pp. 117101.
Elsevier DOI Code:
WWW Link. 2402
Video quality assessment, High frame rate, No reference/blind, Temporal band-pass filter, Natural scene statistics, Generalized Gaussian distribution BibRef


Wu, H.[Haoning], Zhang, E.[Erli], Liao, L.[Liang], Chen, C.F.[Chao-Feng], Hou, J.W.[Jing-Wen], Wang, A.[Annan], Sun, W.X.[Wen-Xiu], Yan, Q.[Qiong], Lin, W.S.[Wei-Si],
Exploring Video Quality Assessment on User Generated Contents from Aesthetic and Technical Perspectives,
ICCV23(20087-20097)
IEEE DOI Code:
WWW Link. 2401
BibRef

Yang, Y.[Yang], Jiang, B.[Bo], Wu, K.[Kailin],
Prnet: A Progressive Regression Network for No-Reference User-Generated-Content (UGC) Video Quality Assessment,
ICIP23(640-644)
IEEE DOI 2312
BibRef

Zhang, Z.C.[Zi-Cheng], Zhou, Y.J.[Ying-Jie], Sun, W.[Wei], Min, X.K.[Xiong-Kuo], Zhai, G.T.[Guang-Tao],
Geometry-Aware Video Quality Assessment for Dynamic Digital Human,
ICIP23(1365-1369)
IEEE DOI 2312
BibRef

Pasquarella, V.J.[Valerie J.], Brown, C.F.[Christopher F.], Czerwinski, W.[Wanda], Rucklidge, W.J.[William J.],
Comprehensive quality assessment of optical satellite imagery using weakly supervised video learning,
EarthVision23(2125-2135)
IEEE DOI 2309
BibRef

Agarla, M.[Mirko], Celona, L.[Luigi], Rota, C.[Claudio], Schettini, R.[Raimondo],
Quality assessment of enhanced videos guided by aesthetics and technical quality attributes,
NTIRE23(1533-1541)
IEEE DOI 2309
BibRef

Li, Z.[Zutong], Yang, L.[Lei],
DCVQE: A Hierarchical Transformer for Video Quality Assessment,
ACCV22(IV:398-416).
Springer DOI 2307
BibRef

Fontanel, D.[Dario], Higham, D.[David], Vallade, B.Q.A.[Benoit Quentin Arthur],
On the Importance of Spatio-Temporal Learning for Video Quality Assessment,
VAQuality23(1-7)
IEEE DOI 2302
Correlation, Conferences, User-generated content, Quality assessment, Reliability, Video recording BibRef

Han, X.H.[Xiao-Hao], Zhang, W.[Wei], Pu, J.[Jian],
Compressed Video Quality Enhancement with Motion Approximation and Blended Attention,
ICPR22(338-344)
IEEE DOI 2212
Deep learning, Fluctuations, Neural networks, Feature extraction, Robustness, Quality assessment BibRef

Han, X.H.[Xiao-Hao], Zhang, W.[Wei], Pu, J.[Jian],
Exploring Spatiotemporal Relationships for Improving Compressed Video Quality,
ICPR22(400-406)
IEEE DOI 2212
Interpolation, Benchmark testing, Spatiotemporal phenomena, Quality assessment, Calibration, Data mining, Video recording BibRef

Perrin, A.F.[Anne-Flore], Dormeval, C.[Charles], Wang, Y.[Yilin], Birkbeck, N.[Neil], Adsumilli, B.[Balu], Le Callet, P.[Patrick],
When is the Cleaning of Subjective Data Relevant to Train UGC Video Quality Metrics?,
ICIP22(1466-1470)
IEEE DOI 2211
Visualization, Uncertainty, Biological system modeling, Benchmark testing, Cleaning, Data models, Quality assessment, Training metrics BibRef

Wang, Y.[Yilin], Yim, J.G.[Joong Gon], Birkbeck, N.[Neil], Ke, J.J.[Jun-Jie], Talebi, H.[Hossein], Chen, X.[Xi], Yang, F.[Feng], Adsumilli, B.[Balu],
Revisiting the Efficiency of UGC Video Quality Assessment,
ICIP22(3016-3020)
IEEE DOI 2211
Training, Image coding, Data collection, Distortion, Feature extraction, Data models, Quality assessment, Efficient Network BibRef

Xing, F.C.[Feng-Chuang], Wang, Y.G.[Yuan-Gen], Wang, H.[Hanpin], Li, L.[Leida], Zhu, G.P.[Guo-Pu],
Starvqa: Space-Time Attention for Video Quality Assessment,
ICIP22(2326-2330)
IEEE DOI 2211
Training, Image coding, Video sequences, Transformers, Distortion, video quality assessment, in-the-wild videos, Transformer BibRef

Beghdadi, A.[Azeddine], Qureshi, M.A.[Muhammad Ali], Dakkar, B.E.[Borhen-Eddine], Gillani, H.H.[Hammad Hassan], Khan, Z.A.[Zohaib Amjad], Kaaniche, M.[Mounir], Ullah, M.[Mohib], Cheikh, F.A.[Faouzi Alaya],
A New Video Quality Assessment Dataset for Video Surveillance Applications,
ICIP22(1521-1525)
IEEE DOI 2211
Night vision, Databases, Benchmark testing, Distortion, Video surveillance, Quality assessment, Video Surveillance, Distortion generation BibRef

Wu, X.B.[Xin-Bo], Dong, Z.Y.[Zheng-Yan], Zhang, F.[Fan], Rosin, P.L.[Paul L.], Liu, H.T.[Han-Tao],
Analysis of Video Quality Induced Spatio-Temporal Saliency Shifts,
ICIP22(1581-1585)
IEEE DOI 2211
Video coding, Visualization, Systematics, Databases, Statistical analysis, Gaze tracking, Distortion, Video quality, gaze, eye-tracking BibRef

You, J.Y.[Jun-Yong], Lin, Y.[Yuan],
Efficient Transformer with Locally Shared Attention for Video Quality Assessment,
ICIP22(356-360)
IEEE DOI 2211
Image quality, Databases, Video sequences, Memory management, Transformers, Quality assessment, Attention, Transformer, video quality assessment (VQA) BibRef

Pastor, A.[Andréas], Krasula, L.[Lukáš], Zhu, X.Q.[Xiao-Qing], Li, Z.[Zhi], Le Callet, P.[Patrick],
On the Accuracy of Open Video Quality Metrics for Local Decision in AV1 Video Codec,
ICIP22(4013-4017)
IEEE DOI 2211
Measurement, Maximum likelihood estimation, Image coding, Quality assessment, Electron tubes, Video codecs, Video recording, Open Video Codecs BibRef

Çetinkaya, E.[Ekrem], Nguyen, M.[Minh], Timmerer, C.[Christian],
MoViDNN: A Mobile Platform for Evaluating Video Quality Enhancement with Deep Neural Networks,
MMMod22(II:465-472).
Springer DOI 2203
BibRef

Tu, Z.Z.[Zheng-Zhong], Chen, C.J.[Chia-Ju], Wang, Y.L.[Yi-Lin], Birkbeck, N.[Neil], Adsumilli, B.[Balu], Bovik, A.C.[Alan C.],
Video Quality Assessment of User Generated Content: A Benchmark Study and a New Model,
ICIP21(1409-1413)
IEEE DOI 2201
Visualization, Systematics, Computational modeling, User-generated content, Transfer learning, Benchmark testing, no-reference BibRef

Zhang, Z.C.[Zi-Cheng], Lu, W.[Wei], Sun, W.[Wei], Min, X.K.[Xiong-Kuo], Wang, T.[Tao], Zhai, G.T.[Guang-Tao],
Surveillance Video Quality Assessment Based on Quality Related Retraining,
ICIP22(4278-4282)
IEEE DOI 2211
Head, Databases, Surveillance, Distortion, Multitasking, Video surveillance, Quality assessment, Surveillance videos, video quality assessment BibRef

Yi, F.[Fuwang], Chen, M.[Mianyi], Sun, W.[Wei], Min, X.K.[Xiong-Kuo], Tian, Y.[Yuan], Zhai, G.T.[Guang-Tao],
Attention Based Network for No-Reference UGC Video Quality Assessment,
ICIP21(1414-1418)
IEEE DOI 2201
Databases, User-generated content, Neural networks, Visual systems, Logic gates, Feature extraction, Distortion, attention mechanism BibRef

Tu, Z.Z.[Zheng-Zhong], Chen, C.J.[Chia-Ju], Wang, Y.L.[Yi-Lin], Birkbeck, N.[Neil], Adsumilli, B.[Balu], Bovik, A.C.[Alan C.],
A Temporal Statistics Model for UGC Video Quality Prediction,
ICIP21(1454-1458)
IEEE DOI 2201
Analytical models, Databases, Computational modeling, Image processing, User-generated content, Predictive models, user-generated content BibRef

Bhat, M.[Madhukar], Thiesse, J.M.[Jean-Marc], Le Callet, P.[Patrick],
Combining Video Quality Metrics To Select Perceptually Accurate Resolution In A Wide Quality Range: A Case Study,
ICIP21(2164-2168)
IEEE DOI 2201
Measurement, Radio frequency, Image resolution, Image coding, Diversity reception, Encoding, The adaptive resolution, perceptual performance BibRef

Ying, Z.Q.[Zhen-Qiang], Mandal, M.[Maniratnam], Ghadiyaram, D.[Deepti], Bovik, A.C.[Alan C.],
Patch-VQ: 'Patching Up' the Video Quality Problem,
CVPR21(14014-14024)
IEEE DOI 2111
User-generated content, Streaming media, Predictive models, Distortion, Data models, Quality assessment, Pattern recognition BibRef

Chen, H.M.[Hua-Mei], Chen, G.S.[Gen-She], Blasch, E.[Erik],
On the Development of a Classification Based Automated Motion Imagery Interpretability Prediction,
WAAMI20(75-88).
Springer DOI 2103
Video National Imagery Interpretability Rating Scale -- human analyst based. BibRef

Tang, J., Dong, Y., Xie, R., Gu, X., Song, L., Li, L., Zhou, B.,
Deep Blind Video Quality Assessment for User Generated Videos,
VCIP20(156-159)
IEEE DOI 2102
Feature extraction, Quality assessment, Video recording, Streaming media, Databases, Adaptation models, Kernel, no reference BibRef

Zhou, W., Chen, Z.,
Deep Local and Global Spatiotemporal Feature Aggregation for Blind Video Quality Assessment,
VCIP20(338-341)
IEEE DOI 2102
Quality assessment, Video recording, Feature extraction, Spatiotemporal phenomena, Databases, Indexes, Deep learning, spatiotemporal aggregation BibRef

Wu, W.[Wei], Liu, Z.Z.[Zi-Zheng], Chen, Z.Z.[Zhen-Zhong], Liu, S.[Shan],
No-Reference Video Quality Assessment Based On Similarity Map Estimation,
ICIP20(181-185)
IEEE DOI 2011
Quality assessment, Feature extraction, Video recording, Databases, Image analysis, spatio-temporal pooling BibRef

Wang, X., Wang, K., Yang, B., Li, F.W.B., Liang, X.,
Perceptual Quality Assessment On DIBR Synthesized Videos With Composite Distortions,
ICIP20(186-190)
IEEE DOI 2011
Videos, Distortion, Databases, Quality assessment, Measurement, video quality assessment, objective study BibRef

Yim, J.G., Wang, Y., Birkbeck, N., Adsumilli, B.,
Subjective Quality Assessment for Youtube UGC Dataset,
ICIP20(131-135)
IEEE DOI 2011
Quality assessment, YouTube, Correlation, Video recording, Video compression, Standards, Video quality assessment, Crowd-sourcing BibRef

Li, C.[Chen], Xu, M.[Mai], Jiang, L.[Lai], Zhang, S.[Shanyi], Tao, X.M.[Xiao-Ming],
Viewport Proposal CNN for 360deg Video Quality Assessment,
CVPR19(10169-10178).
IEEE DOI 2002
BibRef

Wang, Q., Yuan, H., Huo, J., Li, P.,
A Fidelity-Assured Rate Distortion Optimization Method for Perceptual-Based Video Coding,
ICIP19(4135-4139)
IEEE DOI 1910
fidelity, perceptual quality, structural similarity (SSIM) index, sum of squared error (SSE), rate distortion optimization (RDO). BibRef

Martinez, H.B., Farias, M.C.Q., Hines, A.,
A No-Reference Autoencoder Video Quality Metric,
ICIP19(1755-1759)
IEEE DOI 1910
no-reference quality metric, autoencoder, video quality, degradations, blind quality metrics BibRef

Tamboli, R.R., Kara, P.A., Cserkaszky, A., Barsi, A., Martini, M.G., Appina, B., Channappayya, S.S., Jana, S.,
3D Objective Quality Assessment of Light Field Video Frames,
3DTV-CON18(1-4)
IEEE DOI 1812
cameras, video signal processing, light field displays, light field content creation, objective metric BibRef

Zhang, F., Moss, F.M., Baddeley, R., Bull, D.R.,
BVI-HD: A Video Quality Database for HEVC Compressed and Texture Synthesized Content,
MultMed(20), No. 10, October 2018, pp. 2620-2630.
IEEE DOI 1810
data compression, high definition video, image sequences, video coding, video signal processing, HEVC compression, synthesis-based compression BibRef

Danier, D.[Duolikun], Zhang, F.[Fan], Bull, D.R.[David R],
BVI-VFI: A Video Quality Database for Video Frame Interpolation,
IP(32), 2023, pp. 6004-6019.
IEEE DOI Code:
WWW Link. 2311
BibRef

Kim, W.[Woojae], Kim, J.Y.[Jong-Yoo], Ahn, S.[Sewoong], Kim, J.[Jinwoo], Lee, S.H.[Sang-Hoon],
Deep Video Quality Assessor: From Spatio-Temporal Visual Sensitivity to a Convolutional Neural Aggregation Network,
ECCV18(I: 224-241).
Springer DOI 1810
BibRef

Nasiri, R.M., Duanmu, Z., Wang, Z.,
Temporal Motion Smoothness and the Impact of Frame Rate Variation on Video Quality,
ICIP18(1418-1422)
IEEE DOI 1809
Motion measurement, Video recording, Quality assessment, Histograms, Correlation, Wavelet transforms, Quality of experience, complex wavelet transform BibRef

Dinh, K.Q., Lee, J., Kim, J., Park, Y., Choi, K.P., Park, J.,
Only-Reference Video Quality Assessment for Video Coding Using Convolutional Neural Network,
ICIP18(2496-2500)
IEEE DOI 1809
Measurement, Encoding, Quality assessment, Video coding, Quantization (signal), Training, Kernel, Video quality assessment, convolutional neural network BibRef

Yang, S.[Shu], Zhao, J.Z.[Jun-Zhe], Jiang, T.T.[Ting-Ting], Wang, J.[Jing], Rahim, T.[Tariq], Zhang, B.[Bo], Xu, Z.J.[Zhao-Ji], Fei, Z.S.[Ze-Song],
An objective assessment method based on multi-level factors for panoramic videos,
VCIP17(1-4)
IEEE DOI 1804
quality of experience, video signal processing, virtual reality, Virtual Reality technology, video quality assessment BibRef

Zhu, Y.[Yun], Wang, Y.F.[Yong-Fang], Shuai, Y.[Yuan],
Blind video quality assessment based on spatio-temporal internal generative mechanism,
ICIP17(305-309)
IEEE DOI 1803
Correlation, Distortion, Predictive models, Quality assessment, Streaming media, Video recording, Visualization, video quality assessment BibRef

Chaabouni, A., Lambert, J., Gaudeau, Y., Tizon, N., Nicholson, D., Moureaux, J.M.,
Quality assessment of MPEG-4 AVC/H.264 and HEVC compressed video in a telemedicine context,
ICIP17(3465-3469)
IEEE DOI 1803
Encoding, Measurement, Medical diagnostic imaging, Observers, Quality assessment, Standards, biomedical image processing BibRef

Ghadiyaram, D., Chen, C., Inguva, S., Kokaram, A.,
A no-reference video quality predictor for compression and scaling artifacts,
ICIP17(3445-3449)
IEEE DOI 1803
Databases, Distortion, Feature extraction, Quality assessment, Streaming media, Video recording, YouTube, H.264 compression, scaling artifacts BibRef

Manthey, R.[Robert], Ritter, M.[Marc], Heinzig, M.[Manuel], Kowerko, D.[Danny],
An Exploratory Comparison of the Visual Quality of Virtual Reality Systems Based on Device-Independent Testsets,
VAMR17(130-140).
Springer DOI 1712
BibRef

Duan, H., Zhai, G., Yang, X., Li, D., Zhu, W.,
IVQAD 2017: An immersive video quality assessment database,
WSSIP17(1-5)
IEEE DOI 1707
Bit rate, Cameras, Databases, Quality assessment, Video recording, Virtual reality, Visual systems, Immersive video, database, quality assessment, virtual, reality BibRef

Bolecek, L., Kufa, J., Kaucarik, F., Ricny, V.,
3D video database with known parametrs,
WSSIP17(1-5)
IEEE DOI 1707
Brightness, Databases, Silicon, Video sequences, Visualization, content, database, quality of experience, stereo, subjective, test BibRef

Liu, D.W.[Dong-Wei], Klette, R.,
Sharpness and contrast measures on videos,
ICVNZ15(1-6)
IEEE DOI 1701
computer graphics BibRef

Mustafa, A.[Aamir], Mikhailiuk, A.[Aliaksei], Iliescu, D.A.[Dan Andrei], Babbar, V.[Varun], Mantiuk, R.K.[Rafal K.],
Training a Task-Specific Image Reconstruction Loss,
WACV22(21-30)
IEEE DOI 2202
Training, Image resolution, Semantics, Transform coding, Observers, Feature extraction, Distortion, Computational Photography, Image Processing -> Image Restoration BibRef

Mantiuk, R.K.[Rafal K.],
Practicalities of predicting quality of high dynamic range images and video,
ICIP16(904-908)
IEEE DOI 1610
Brightness BibRef

Kim, H.G., Ro, Y.M.,
Measurement of critical temporal inconsistency for quality assessment of synthesized video,
ICIP16(1027-1031)
IEEE DOI 1610
Distortion BibRef

Polok, L.[Lukas], Klicnar, L.[Lukas], Beran, V.[Vitezslav], Smrz, P.[Pavel], Zemcik, P.[Pavel],
Quality assurance in large collections of video sequences,
ICIP15(3580-3584)
IEEE DOI 1512
automatic quality assurance; large video databases; time synchronization BibRef

Wang, M.M.[Meng-Meng], Zhang, F.[Fan], Agrafiotis, D.[Dimitris],
A very low complexity reduced reference video quality metric based on spatio-temporal information selection,
ICIP15(571-575)
IEEE DOI 1512
Video quality assessment BibRef

Talens-Noguera, J.V.[Juan V.], Zhang, W.[Wei], Liu, H.T.[Han-Tao],
Studying human behavioural responses to time-varying distortions for video quality assessment,
ICIP15(651-655)
IEEE DOI 1512
Video quality assessment BibRef

Mirkovic, M.[Milan], Culibrk, D.[Dubravko], Sladojevic, S.[Srdjan], Anderla, A.[Andras],
Video Quality Assessment for Mobile Devices on Mobile Devices,
QoEM15(555-562).
Springer DOI 1511
BibRef

Xu, M.[Mai], Zhang, J.Z.[Jing-Ze], Ma, Y.[Yuan], Wang, Z.L.[Zu-Lin],
A novel objective quality assessment method for perceptual video coding in conversational scenarios,
VCIP14(29-32)
IEEE DOI 1504
Gaussian processes BibRef

Zhu, K.F.[Kong-Feng], Barkowsky, M.[Marcus], Shen, M.[Minmin], Le Callet, P.[Patrick], Saupe, D.[Dietmar],
Optimizing feature pooling and prediction models of VQA algorithms,
ICIP14(541-545)
IEEE DOI 1502
Databases BibRef

Mittal, A.[Anish], Saad, M.[Michele], Bovik, A.C.[Alan C.],
Assessment of video naturalness using time-frequency statistics,
ICIP14(571-574)
IEEE DOI 1502
Computational modeling BibRef

Yeganeh, H.[Hojatollah], Kordasiewicz, R.[Roman], Gallant, M.[Michael], Ghadiyaram, D.[Deepti], Bovik, A.C.[Alan C.],
Delivery quality score model for Internet video,
ICIP14(2007-2011)
IEEE DOI 1502
Delays BibRef

Irvine, J.M., Wood, R.J., Reed, D., Lepanto, J.,
Video image quality analysis for enhancing tracker performance,
AIPR13(1-9)
IEEE DOI 1408
object tracking BibRef

Cardoso, J.V.M., Alencar, M.S., Regis, C.D.M., Oliveira, I.P.,
Temporal analysis and perceptual weighting for objective video quality measurement,
Southwest14(57-60)
IEEE DOI 1406
IP networks BibRef

Zerman, E.[Emin], Konuk, B.[Baris], Nur, G.[Gokce], Akar, G.B.[Gozde Bozdagi],
A parametric video quality model based on source and network characteristics,
ICIP14(595-599)
IEEE DOI 1502
BibRef
Earlier: A2, A1, A3, A4:
A spatiotemporal no-reference video quality assessment model,
ICIP13(54-58)
IEEE DOI 1402
Databases. Bit rate BibRef

Besson, A.[Adrien], de Simone, F.[Francesca], Ebrahimi, T.[Touradj],
Objective quality metrics for video scalability,
ICIP13(59-63)
IEEE DOI 1402
Measurement BibRef

Stapenhurst, R.[Robert], Lu, J.[Jinyun], Agrafiotis, D.[Dimitris],
Performance evaluation of objective video quality metrics on mixed spatiotemporal resolution content,
ICIP13(64-68)
IEEE DOI 1402
Measurement BibRef

McLaughlin, L.[Linda], Hemami, S.S.[Sheila S.],
Reduced-reference quality assessment with scalable overhead for video with packet loss,
ICIP13(1622-1626)
IEEE DOI 1402
H.264 BibRef

Zeng, K.[Kai], Wang, Z.[Zhou],
3D-SSIM for video quality assessment,
ICIP12(621-624).
IEEE DOI 1302
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Ou, Y.F.[Yen-Fu], Zeng, H.Q.[Hui-Qi], Wang, Y.[Yao],
Perceptual quality of video with quantization variation: A subjective study and analytical modeling,
ICIP12(1505-1508).
IEEE DOI 1302
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Ukhanova, A.[Anna], Korhonen, J.[Jari], Forchhammer, S.[Soren],
Objective assessment of the impact of frame rate on video quality,
ICIP12(1513-1516).
IEEE DOI 1302
BibRef

You, J.[Junyong], Ebrahimi, T.[Touradj], Perkis, A.[Andrew],
Video quality metric based on fixation prediction and foveal imaging,
ICIP12(1509-1512).
IEEE DOI 1302
BibRef

Chen, J.W.[Jian-Wen], Xu, F.[Feng], Zhu, H.[Hao], Mo, Y.J.[Yi-Jun],
An adaptive visual quality optimization method for Internet video applications,
VCIP12(1-6).
IEEE DOI 1302
BibRef

Seshadrinathan, K.[Kalpana], Caviedes, J.E.[Jorge E.],
Control of video processing algorithms based on measured perceptual quality characteristics,
Southwest12(177-180).
IEEE DOI 1205
BibRef

Chen, M.J.[Ming-Jun], Kwon, D.K.[Do-Kyoung], Bovik, A.C.[Alan C.],
Study of subject agreement on stereoscopic video quality,
Southwest12(173-176).
IEEE DOI 1205
BibRef

Park, J.[Jincheol], Seshadrinathan, K.[Kalpana], Lee, S.H.[Sang-Hoon], Bovik, A.C.[Alan C.],
Spatio-temporal quality pooling accounting for transient severe impairments and egomotion,
ICIP11(2509-2512).
IEEE DOI 1201
Not just one frame. BibRef

Vu, P.V.[Phong V.], Vu, C.T.[Cuong T.], Chandler, D.M.[Damon M.],
A spatiotemporal most-apparent-distortion model for video quality assessment,
ICIP11(2505-2508).
IEEE DOI 1201
BibRef

You, J.Y.[Jun-Yong], Korhonen, J.[Jari], Reiter, U.[Ulrich],
Audiovisual quality fusion based on relative multimodal complexity,
ICIP11(3337-3340).
IEEE DOI 1201
BibRef

Sugimoto, O.[Osamu], Naito, S.[Sei],
No reference metric of video coding quality based on parametric analysis of video bitstream,
ICIP11(3333-3336).
IEEE DOI 1201
BibRef

Horch, C.[Clemens], Keimel, C.[Christian], Habigt, J.[Julian], Diepold, K.[Klaus],
Length-independent refinement of video quality metrics based on multiway data analysis,
ICIP13(44-48)
IEEE DOI 1402
Feature extraction BibRef

Birklbauer, C.[Clemens], Grosse, M.[Max], Grundhöfer, A.[Anselm], Liu, T.L.[Tian-Lun], Bimber, O.[Oliver],
Display Pixel Caching,
ISVC11(I: 66-77).
Springer DOI 1109
for TV, user evaluations. BibRef

de Silva, D.V.S.X., Fernando, W.A.C., Worrall, S.T., Kondoz, A.M.,
A novel depth map quality metric and its usage in depth map coding,
3DTV11(1-4).
IEEE DOI 1105
BibRef

You, J.Y.[Jun-Yong], Hannuksela, M.M.[Miska M.], Gabbouj, M.[Moncef],
An objective video quality metric based on spatiotemporal distortion,
ICIP09(2229-2232).
IEEE DOI 0911
BibRef

Osamu, Naito, S.[Sei], Sakazawa, S.[Shigeyuki], Koike, A.[Atsushi],
Objective perceptual video quality measurement method based on hybrid no reference framework,
ICIP09(2237-2240).
IEEE DOI 0911
BibRef

Yao, J.X.[Ji-Xian], Zhang, Y.[Yuan], Xu, G.Z.[Gui-Zhong], Jin, M.[Meng],
No-Reference Objective Quality Assessment for Video Communication Services Based on Feature Extraction,
CISP09(1-6).
IEEE DOI 0910
BibRef

Irvine, J.M., Fenimore, C., Cannon, D., Roberts, J., Israel, S.A., Simon, L., Watts, C., Miller, J.D., Brennan, M., Aviles, A.I., Tighe, P.F., Behrens, R.J.,
Feasibility study for the development of a motion imagery quality metric,
AIPR04(179-183).
IEEE DOI 0410
BibRef

Punchihewa, A., Armstrong, J.,
Effects of sub-sampling and quantisation on colour bleeding due to image and video compression,
IVCNZ08(1-6).
IEEE DOI 0811
BibRef

Gustafsson, J.[Jorgen], Heikkila, G.[Gunnar], Pettersson, M.[Martin],
Measuring multimedia quality in mobile networks with an objective parametric model,
ICIP08(405-408).
IEEE DOI 0810
BibRef

Duplaga, M.[Mariusz], Leszczuk, M.[Mikolaj], Papir, Z.[Zdzislaw], Przelaskowski, A.[Artur],
Evaluation of Quality Retaining Diagnostic Credibility for Surgery Video Recordings,
Visual08(xx-yy).
Springer DOI 0809
BibRef

Schallauer, P.[Peter], Bailer, W.[Werner], Morzinger, R.[Roland], Furntratt, H.[Hermann], Thallinger, G.[Georg],
Automatic Quality Analysis for Film and Video Restoration,
ICIP07(IV: 9-12).
IEEE DOI 0709
BibRef

Ong, E.P.[Ee-Ping], Lin, W.S.[Wei-Si], Lu, Z.K.[Zhong-Kang], Yao, S.[Susu],
Colour Perceptual Video Quality Metric,
ICIP05(III: 1172-1175).
IEEE DOI 0512
BibRef

Feghali, R., Wang, D., Speranza, F., Vincent, A.,
Quality Metric for Video Sequences with Temporal Scalability,
ICIP05(III: 137-140).
IEEE DOI 0512
BibRef

Zhong, Y.[Ying], Richardson, I.E.[Iain E.], Sahraie, A.[Arash], McGeorge, P.[Peter],
Influence of Task and Scene Content on Subjective Video Quality,
ICIAR04(I: 295-301).
Springer DOI 0409
BibRef

Kim, K.N.[Kyung-Nam], Davis, L.S.,
A fine-structure image/video quality measure using local statistics,
ICIP04(V: 3535-3538).
IEEE DOI 0505
BibRef

Ojansivu, V., Silven, O., Huotari, R.,
A technique for digital video quality evaluation,
ICIP03(III: 181-184).
IEEE DOI 0312
BibRef

Watson, A.B., Malo, J.,
Video quality measures based on the standard spatial observer,
ICIP02(III: 41-44).
IEEE DOI 0210
BibRef

Moore, M.S., Mitra, S.K., Foley, J.M.,
Defect visibility and content importance implications for the design of an objective video fidelity metric,
ICIP02(III: 45-48).
IEEE DOI 0210
BibRef

Celidonio, M.[Massimo], Santella, G.[Giovanni],
On the Correlation between Transmission Quality-of-Service (QoS) Parameters and Image Quality of Digitally Transmitted Video in Radio Terrestrial Broadcasting,
ICIP96(III: 327-330).
IEEE DOI BibRef 9600

Osberger, W., Maeder, A.J., McLean, D.,
An objective quality assessment technique for digital image sequences,
ICIP96(I: 897-900).
IEEE DOI 9610
BibRef

Cotton, B.,
A two-stage objective model for video quality evaluation,
ICIP96(I: 893-896).
IEEE DOI 9610
BibRef

Chapter on Image Processing, Restoration, Enhancement, Filters, Image and Video Coding continues in
Video Quality for Stereo, 3D Video .


Last update:Mar 16, 2024 at 20:36:19