Dr Hantao Liu

2021

• Lévêque, L.et al. 2021. Comparative study of the methodologies used for subjective medical image quality assessment. Physics in Medicine and Biology 66(15), article number: 15TR02. (10.1088/1361-6560/ac1157)
• Guo, P.et al. 2021. Underwater image quality assessment: subjective and objective methods. IEEE Transactions on Multimedia (10.1109/TMM.2021.3074825)
• Lou, J.et al. 2021. Study of saccadic eye movements in diagnostic imaging. Presented at: 2021 IEEE International Conference on Image Processing (ICIP), Anchorage, AK, USA, 19-22 September 2021.
• Guo, P.et al. 2021. A metric for quantifying image quality induced saliency variation. Presented at: 2021 IEEE International Conference on Image Processing (ICIP), Anchorage, AK, USA, 19-22 September 2021.
• Xiang, T., Yang, Y. and Liu, H. 2021. PRNet: a progressive recovery network for revealing perceptually encrypted images. Presented at: ACM Multimedia 2021, Chengdu, China, 20-24 October 2021.
• Guo, P.et al. 2021. Convex optimization method for quantifying image quality induced saliency variation. IEEE Access 9, pp. 111533-111543. (10.1109/ACCESS.2021.3102465)
• Yang, X., Li, F. and Liu, H. 2021. A measurement for distortion induced saliency variation in natural images. IEEE Transactions on Instrumentation and Measurement 70, article number: 5015814. (10.1109/TIM.2021.3108538)

2020

• Yang, X., Li, F. and Liu, H. 2020. TTL-IQA: transitive transfer learning based no-reference image quality assessment. IEEE Transactions on Multimedia (10.1109/TMM.2020.3040529)
• Guo, P.et al. 2020. Multi-scale enhancement fusion for underwater sea cucumber images based on human visual system modelling. Computers and Electronics in Agriculture 175, article number: 105608. (10.1016/j.compag.2020.105608)
• Yang, X., Li, F. and Liu, H. 2020. Deep feature importance awareness based no-reference image quality prediction. Neurocomputing 401, pp. 209-223. (10.1016/j.neucom.2020.03.072)
• Xia, Z.et al. 2020. Towards accurate quality estimation of screen content pictures with very sparse reference information. IEEE Transactions on Industrial Electronics 37(3), pp. 2251-2261. (10.1109/TIE.2019.2905831)
• Gu, K.et al. 2020. Multiscale natural scene statistical analysis for no-reference quality evaluation of DIBR-synthesized views. IEEE Transactions on Broadcasting 66(1), pp. 127-139. (10.1109/TBC.2019.2906768)
• Lévêque, L.et al. 2020. CUID: a new study of perceived image quality and its subjective assessment. Presented at: 27th IEEE International Conference on Image Processing (ICIP 2020), United Arab Emirates, 25-28 October 2020.
• Zhao, X.et al. 2020. Deep learning vs. traditional algorithms for saliency prediction of distorted images. Presented at: 27th IEEE International Conference on Image Processing (ICIP 2020), United Arab Emirates, 25-28 October 2020.
• Lévêque, L., Young, P. and Liu, H. 2020. Studying the gaze patterns of expert radiologists in screening mammography: a case study with Breast Test Wales. Presented at: 28th European Signal Processing Conference (EUSIPCO 2020), Amsterdam, Netherlands, 18-22 Janurary 2021.

2019

• Zhu, Z.et al. 2019. A metric for video blending quality assessment. IEEE Transactions on Image Processing 29, pp. 3014-3022. (10.1109/TIP.2019.2955294)
• Lévêque, L.et al. 2019. A statistical evaluation of eye-tracking data of screening mammography: Effects of expertise and experience on image reading. Signal Processing: Image Communication 78, pp. 86-93. (10.1016/j.image.2019.06.008)
• Yue, G.et al. 2019. No-reference quality evaluator of transparently encrypted images. IEEE Transactions on Multimedia 21(9), pp. 2184-2194. (10.1109/TMM.2019.2913315)
• Hu, B.et al. 2019. Pairwise-comparison-based rank learning for benchmarking image restoration algorithms. IEEE Transactions on Multimedia 21(8), pp. 2042-2056. (10.1109/TMM.2019.2894958)
• Yang, X., Li, F. and Liu, H. 2019. A comparative study of dnn-based models for blind image quality prediction. Presented at: The 26th IEEE International Conference on Image Processing (ICIP), Taipei, Taiwan, 22-25 September 2019.
• Liu, H. and Leveque, L. 2019. An eye-tracking database of video advertising. Presented at: 26th IEEE International Conference on Image Processing (ICIP), Taipei, Taiwan, 22-25 September 2019.
• Zhang, W.et al. 2019. The effect of spatio-temporal inconsistency on the subjective quality evaluation of omnidirectional videos. Presented at: 2019 IEEE International Conference on Acoustics, Speech and Signal Processing, Brighton, UK, 12-17 May 2019ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). Piscataway, NJ: IEEE pp. 4055-4059., (10.1109/ICASSP.2019.8682221)
• Zhou, Y.et al. 2019. No-reference quality assessment for contrast-distorted images based on multifaceted statistical representation of structure. Journal of Visual Communication and Image Representation 60, pp. 158-169. (10.1016/j.jvcir.2019.02.028)
• Leveque, L., Zhang, W. and Liu, H. 2019. International comparison of radiologists' assessment of the perceptual quality of medical ultrasound video. Presented at: 11th International Conference on Quality of Multimedia Experience (QoMEX 2019), Berlin, Germany, 5-7 June 2019Proceedings of 2019 Eleventh International Conference on Quality of Multimedia Experience (QoMEX). IEEE
• Leveque, L., Zhang, W. and Liu, H. 2019. Subjective assessment of image quality induced saliency variation. Presented at: The 26th IEEE International Conference on Image Processing (ICIP), Taipei, Taiwan, 22-25 September 2019.
• Yang, M.et al. 2019. Preselection based subjective preference evaluation for the quality of underwater images. Presented at: IEEE Conference on Computer Vision and Pattern Recognition, Long Beach, CA, 16 - 20 June 2019. pp. -.
• Yang, X., Li, F. and Liu, H. 2019. A survey of DNN methods for blind image quality assessment. IEEE Access 7, pp. 123788-123806. (10.1109/ACCESS.2019.2938900)

2018

• Zhang, T.et al. 2018. Depth-of-field effect in subjective and objective evaluation of image quality. Presented at: ACM RACS 2018 : 2018 ACM Research in Adaptive and Convergent Systems, Honololu, HI, USA, 9-12 October 2018RACS '18: Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems. New York: ACM pp. 308-312., (10.1145/3264746.3264757)
• Leveque, L.et al. 2018. On the subjective assessment of the perceived quality of medical images and videos. Presented at: 10th International Conference on Quality of Multimedia Experience (QoMEX 2018), Cagliari, Italy, 29 May-1 June 20182018 Tenth International Conference on Quality of Multimedia Experience (QoMEX). Piscataway, NJ: IEEE, (10.1109/QoMEX.2018.8463297)
• Yu, Y.et al. 2018. Perceptual quality and visual experience analysis for polygon mesh on different display devices. IEEE Access 6, pp. 42941-42949. (10.1109/ACCESS.2018.2859254)
• Zhang, W., Martin, R. R. and Liu, H. 2018. A saliency dispersion measure for improving saliency-based image quality metrics. IEEE Transactions on Circuits and Systems for Video Technology 28(6), pp. 1462-1466. (10.1109/TCSVT.2017.2650910)
• Zhu, Z.et al. 2018. A comparative study of algorithms for realtime panoramic video blending. IEEE Transactions on Image Processing 27(6), pp. 2952-2965. (10.1109/TIP.2018.2808766)
• Leveque, L.et al. 2018. State of the art: Eye-tracking studies in medical imaging. IEEE Access 6, pp. 37023-37034. (10.1109/ACCESS.2018.2851451)

2017

• Leveque, L.et al. 2017. Video quality perception in telesurgery. Presented at: 2017 IEEE 19th International Workshop on Multimedia Signal Processing (MMSP), Luton, UK, 16-18 October 20172017 IEEE 19th International Workshop on Multimedia Signal Processing (MMSP). IEEE, (10.1109/MMSP.2017.8122219)
• Liu, H. and Wang, Z. 2017. Perceptual quality assessment of medical images. In: Caplan, M. ed. Reference Module in Biomedical Sciences. Elsevier, (10.1016/B978-0-12-801238-3.64099-0)
• Leveque, L.et al. 2017. The impact of specialty settings on the perceived quality of medical ultrasound video. IEEE Access 5, pp. 16998-17005. (10.1109/ACCESS.2017.2743264)
• Zhang, W. and Liu, H. 2017. Learning picture quality from visual distraction: Psychophysical studies and computational models. Neurocomputing 247, pp. 183-191. (10.1016/j.neucom.2017.03.054)
• Leveque, L.et al. 2017. Study of video quality assessment for telesurgery. IEEE Access 5, pp. 9990-9999. (10.1109/ACCESS.2017.2704285)
• Zhang, W. and Liu, H. 2017. Towards a reliable collection of eye-tracking data for image quality research: challenges, solutions and applications. IEEE Transactions on Image Processing 26(5), pp. 2424-2437. (10.1109/TIP.2017.2681424)
• Zhang, W. and Liu, H. 2017. Study of saliency in objective video quality assessment. IEEE Transactions on Image Processing 26(3), pp. 1275-1288. (10.1109/TIP.2017.2651410)
• Zhang, W. and Liu, H. 2017. Saliency in objective video quality assessment: What is the ground truth?. Presented at: 2016 IEEE 18th International Workshop on Multimedia Signal Processing (MMSP), Montreal, QC, Canada, 21-23 September 20162016 IEEE 18th International Workshop on Multimedia Signal Processing (MMSP). IEEE, (10.1109/MMSP.2016.7813333)
• Zhang, W. and Liu, H. 2017. SIQ288: A saliency dataset for image quality research. Presented at: 2016 IEEE 18th International Workshop on Multimedia Signal Processing (MMSP), Montreal, QC, Canada, 21-23 September 20162016 IEEE 18th International Workshop on Multimedia Signal Processing (MMSP). IEEE, (10.1109/MMSP.2016.7813334)

2016

• Liu, H.et al. 2016. The relative impact of ghosting and noise on the perceived quality of MR images. IEEE Transactions on Image Processing 25(7), pp. 3087-3098. (10.1109/TIP.2016.2561406)
• Lavoue, G.et al. 2016. Quality assessment and perception in computer graphics. IEEE Computer Graphics and Applications 36(4), pp. 21-22. (10.1109/MCG.2016.72)
• Zhang, W.et al. 2016. The application of visual saliency models in objective image quality assessment: a statistical evaluation. IEEE Transactions on Neural Networks and Learning Systems 27(6), pp. 1266-1278. (10.1109/TNNLS.2015.2461603)
• Zhang, W.et al. 2016. Benchmarking state-of-the-art visual saliency models for image quality assessment. Presented at: 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Shanghai, China, 20-25 March 20162016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE pp. 1090-1094., (10.1109/ICASSP.2016.7471844)

2015

• Zhang, W., Talens-Noguera, J. V. and Liu, H. 2015. The quest for the integration of visual saliency models in objective image quality assessment: A distraction power compensated combination strategy. Presented at: 2015 IEEE International Conference on Image Processing (ICIP), Quebec City, QC, Canada, 27-30 September 20152015 IEEE International Conference on Image Processing (ICIP). IEEE pp. 1250., (10.1109/ICIP.2015.7351000)
• Talens-Noguera, J. V., Zhang, W. and Liu, H. 2015. Studying human behavioural responses to time-varying distortions for video quality assessment. Presented at: 2015 IEEE International Conference on Image Processing (ICIP), Quebec City, QC, Canada, 27-30 September 20152015 IEEE International Conference on Image Processing (ICIP). IEEE pp. 651., (10.1109/ICIP.2015.7350879)
• Rogowitz, B. E.et al. 2015. Perceived interest versus overt visual attention in image quality assessment. Presented at: SPIE/IS&T Electronic Imaging 2015, San Francisco, California, 8-12 February 2015. Society of Photo-optical Instrumentation Engineers (SPIE), (10.1117/12.2086371)
• Zhang, W.et al. 2015. Studying the added value of computational saliency in objective image quality assessment. Presented at: 2014 IEEE Visual Communications and Image Processing Conference, Valletta, Malta, 7-10 December 20142014 IEEE Visual Communications and Image Processing Conference. IEEE pp. 21., (10.1109/VCIP.2014.7051494)
• Alers, H.et al. 2015. Effects of task and image properties on visual-attention deployment in image-quality assessment. Journal of Electronic Imaging 24(2), article number: 23030. (10.1117/1.JEI.24.2.023030)

2014

• Talens-Noguera, J. V. and Liu, H. 2014. Studying the perceived quality variation over time for video quality assessment. Presented at: PIVP '14 Proceedings of the 1st International Workshop on Perception Inspired Video Processing, Orlando, Florida, 07 November 2014PIVP '14 Proceedings of the 1st International Workshop on Perception Inspired Video Processing. New York: ACM pp. 35-36., (10.1145/2662996.2663013)

2013

• Alers, H.et al. 2013. Studying the effect of optimizing image quality in salient regions at the expense of background content. Journal of Electronic Imaging 22(4), article number: 43012. (10.1117/1.JEI.22.4.043012)
• Engelke, U.et al. 2013. Comparative study of fixation density maps. IEEE Transactions on Image Processing 22(3), pp. 1121-1133. (10.1109/TIP.2012.2227767)
• Liu, H.et al. 2013. How does image content affect the added value of visual attention in objective image quality assessment?. IEEE Signal Processing Letters 20(4), pp. 355-358. (10.1109/LSP.2013.2243725)

2012

• Liu, H. and Heynderickx, I. 2012. Towards an efficient model of visual saliency for objective image quality assessment. Presented at: 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Kyoto, Japan, 25-30 March 20122012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE pp. 1153-1153., (10.1109/ICASSP.2012.6288091)
• Abbey, C. K.et al. 2012. Studying the relative impact of ghosting and noise on the perceived quality of MR images. Presented at: SPIE Medical Imaging 2012, San Diego, California, 4-9 February 2012, Vol. 8318. Society of Photo-optical Instrumentation Engineers (SPIE), (10.1117/12.911019)
• Liu, H. and Heynderickx, I. 2012. Does variation in quality scores result from variation in visual attention?. Presented at: Sixth International Workshop on Video Processing and Quality Metrics for Consumer Electronics, Scottsdale, Arizona, 19-20 January 2012. pp. -.

2011

• Liu, H.et al. 2011. An efficient no-reference metric for perceived blur. Presented at: 3rd European Workshop on Visual Information Processing 2011, Paris, France, 4-6 July 20113rd European Workshop on Visual Information Processing Proceedings. IEEE pp. 174., (10.1109/EuVIP.2011.6045525)
• Liu, H.et al. 2011. Efficient neural-network-based no-reference approach to an overall quality metric for JPEG and JPEG2000 compressed images. Journal of Electronic Imaging 20(4), article number: 43007. (10.1117/1.3664181)
• Liu, H. and Heynderickx, I. 2011. Visual attention in objective image quality assessment: based on eye-tracking data. IEEE Transactions on Circuits and Systems for Video Technology 21(7), pp. 971-982. (10.1109/TCSVT.2011.2133770)
• Rogowitz, B. E.et al. 2011. Interactions of visual attention and quality perception. Presented at: IS&T/SPIE Electronic Imaging, 2011, San Francisco Airport, California, 23 - 27 January 2011. Society of Photo-optical Instrumentation Engineers (SPIE), (10.1117/12.876712)
• Engelke, U.et al. 2011. Comparing two eye-tracking databases: The effect of experimental setup and image presentation time on the creation of saliency maps. Presented at: 28th Picture Coding Symposium 2010, Nagoya, Japan, 8-10 December 201028th Picture Coding Symposium Proceedings. IEEE pp. 282., (10.1109/PCS.2010.5702487)
• Farnand, S. P.et al. 2011. Issues in the design of a no-reference metric for perceived blur. Presented at: IS&T/SPIE Electronic Imaging, 2011, San Francisco Airport, California, 23 - 27 January 2011. Society of Photo-optical Instrumentation Engineers (SPIE), (10.1117/12.873277)
• Liu, H. 2011. Modeling perceived quality for imaging applications. Delft University of Technology.

2010

• Liu, H., Klomp, N. and Heynderickx, I. 2010. A perceptually relevant approach to ringing region detection. IEEE Transactions on Image Processing 19(6), pp. 1414-1426. (10.1109/TIP.2010.2041406)
• Liu, H., Klomp, N. and Heynderickx, I. 2010. A no-reference metric for perceived ringing artifacts in images. IEEE Transactions on Circuits and Systems for Video Technology 20(4), pp. 529-539. (10.1109/TCSVT.2009.2035848)
• Rogowitz, B. E.et al. 2010. No-reference image quality assessment based on localized gradient statistics: application to JPEG and JPEG2000. Presented at: IS&T/SPIE Electronic Imaging Conference 2010, San Jose, California, 17-21 January 2010. Society of Photo-optical Instrumentation Engineers (SPIE), (10.1117/12.838982)
• Redi, J.et al. 2010. How to apply spatial saliency into objective metrics for JPEG compressed images?. Presented at: 2009 16th IEEE International Conference on Image Processing (ICIP), Cairo, Egypt, 7 - 10 November 20092009 16th IEEE International Conference on Image Processing (ICIP) Proceedings. IEEE, (10.1109/ICIP.2009.5414035)
• Liu, H. and Heynderickx, I. 2010. Studying the added value of visual attention in objective image quality metrics based on eye movement data. Presented at: 2009 16th IEEE International Conference on Image Processing (ICIP), Cairo, Egypt, 7 - 10 November 20092009 16th IEEE International Conference on Image Processing (ICIP). IEEE pp. 3097., (10.1109/ICIP.2009.5414466)
• Farnand, S. P.et al. 2010. Comparing subjective image quality measurement methods for the creation of public databases. Presented at: IS&T/SPIE Electronic Imaging Conference 2010, San Jose, California, 17-21 January 2010. Society of Photo-optical Instrumentation Engineers (SPIE), (10.1117/12.839195)
• Farnand, S. P.et al. 2010. Studying the effect of optimizing the image quality in saliency regions at the expense of background content. Presented at: IS&T/SPIE Electronic Imaging Conference 2010, San Jose, California, 17-21 January 2010, Vol. 7529. Society of Photo-optical Instrumentation Engineers (SPIE), (10.1117/12.839545)
• Liu, H. and Heynderickx, I. 2010. Visual attention modeled with luminance only: from eye-tracking data to computational models. Presented at: Fifth International Workshop on Video Processing and Quality Metrics for Consumer Electronics, Scottsdale, Arizona, 13-15 January 2010. pp. -.

2009

• Liu, H. and Heynderickx, I. 2009. A perceptually relevant no-reference blockiness metric based on local image characteristics. EURASIP Journal on Advances in Signal Processing 2009(1), article number: 263540. (10.1155/2009/263540)
• Liu, H., Klomp, N. and Heynderickx, I. 2009. A no-reference metric for perceived ringing. Presented at: Fourth International Workshop on Video Processing and Quality Metrics for Consumer Electronics, Scottsdale, Arizona, U.S.A., 14-16 January 2009. pp. -.

2008

• Liu, H., Klomp, N. and Heynderickx, I. 2008. Perceptually relevant ringing region detection method. Presented at: 16th European Signal Processing Conference, Lausanne, 25-29 August 20082008 16th European Signal Processing Conference Proceedings. IEEE pp. -.
• Kiranyaz, S.et al. 2008. An efficient approach for boundary based corner detection by maximizing bending ratio and curvature. Presented at: 2007 9th International Symposium on Signal Processing and Its Applications, Sharjah, United Arab Emirates, 12-15 February 20072007 9th International Symposium on Signal Processing and Its Applications. IEEE pp. 1., (10.1109/ISSPA.2007.4555467)
• Liu, H. and Heynderickx, I. 2008. A no-reference perceptual blockiness metric. Presented at: 2008 IEEE International Conference on Acoustics, Speech and Signal Processing, Las Vegas, NV, USA, 31 March - 4 April 20082008 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE pp. 865-., (10.1109/ICASSP.2008.4517747)

2007

• Liu, H. and Heynderickx, I. 2007. A simplified human vision model applied to a blocking artifact metric. Presented at: CAIP 2007, Vienna, Austria, 27-29 Aug 2007 Presented at Kropatsch, W. G., Kampel, M. and Hanbury, A. eds.Computer Analysis of Images and Patterns, Vol. 4673. Lecture Notes in Computer Science Berlin, Heidelberg: Springer Verlag pp. 334-341., (10.1007/978-3-540-74272-2_42)