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基于视觉注意力变化的网络丢包视频质量评估

DOI: 10.3724/SP.J.1004.2011.01322, PP. 1322-1331

Keywords: 视觉显著性,注意力变化,视频质量评估,网络丢包损伤

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Abstract:

?针对网络中受丢包损伤的视频提出了一种基于视觉注意力变化的全参考客观质量评估方法.该方法基于视觉显著性检测在视频数据上的应用,考察受网络丢包失真影响的视频数据与标准参考数据在空间和时间上引起的视觉注意力变化,并根据此变化相应的视觉显著性在空间和时间上的差异,提出了一组客观质量评估方法.文中采用17个受丢包损伤的视频数据进行测试,并实施了主观评价实验作为评价标准.与传统的没有考虑人眼视觉显著特性的质量评估方法,以及目前主流的基于视觉显著区域/感兴趣区域对失真像素进行加权的方法进行对比,实验结果表明,基于视觉注意力变化的方法较后两者与主观质量评估结果有更好的相关性,能够更有效地评估丢包损伤视频的质量.

References

[1]  Lu Liu-Ming, Lu Xiao-Yuan. Quality evaluation of video over a packet network based on packet loss. Journal of Image and Graphics, 2009, 14(1): 52-58(卢刘明, 陆肖元. 基于网络丢包的网络视频质量评估. 中国图象图形学报, 2009, 14(1): 52-58)
[2]  Wolf S, Pinson M. Video Quality Measurement Techniques, NTIA-Report 02-392, National Telecommunications and Information Administration, USA, 2002
[3]  RUI Hua-Xia LI Chong-Rong QIU Sheng-Ke. Evaluation of packet loss impairment on streaming video. Journal of Zhejiang University —— Science A, 2006, 7(Suppl.1): 131-136
[4]  Kanumuri S, Cosman P C, Reibman A R, Vaishampayan V A. Modeling packet-loss visibility in MPEG-2 video. IEEE Transactions on Multimedia, 2006, 8(2): 341-355
[5]  Moorthy A K, Seshadrinathan K, Soundararajan R, Bovik A C, Cormack L K. LIVE video quality database [Online], available: http://live.ece.utexas.edu/ research/quality/live_video.html, September 17, 2010
[6]  You J Y, Korhonen J, Perkis A. Spatial and temporal pooling of image quality metrics for perceptual video quality assessment on packet loss streams. In: Proceedings of the IEEE International Conference on Acoustics Speech and Signal Processing. Texas, USA: IEEE, 2010. 1002-1005
[7]  Ling Yun, Xia Jun, Tu Yan, Yin Han-Chun. Detection of region of interest and its application in video image quality assessment. Journal of Southeast University (Natural Science), 2009, 39(4): 754-757(凌云, 夏军, 屠彦, 尹涵春. 视觉感兴趣区的提取及其在视频图像质量评估中的应用. 东南大学学报(自然科学版), 2009, 39(4): 754-757)
[8]  Moorthy A K, Bovik A C. Visual importance pooling for image quality assessment. IEEE Journal of Selected Topics in Signal Processing, 2009, 3(2): 193-201
[9]  Itti L, Koch C, Niebur E. A model of saliency-based visual attention for rapid scene analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1998, 20(11): 1254-1259
[10]  Borst A. Models of motion detection. Nature Neuroscience, 2000, 3: 1168-1168
[11]  Liu Y, Bu J J, Chen C, Mo L J, He K W. Multiframe error concealment for whole-frame loss in H.264/AVC. In: Proceedings of the IEEE International Conference on Image Processing. San Antonio, USA: IEEE, 2007. 281-284
[12]  Itti L, Baldi P. A principle approach to detecting surprising events in video. In: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. San Diego, USA: IEEE, 2005. 631-637
[13]  Ninassi A, Le Meur O, Le Callet P, Barba D. Considering temporal variations of spatial visual distortions in video quality assessment. IEEE Journal of Selected Topics in Signal Processing, 2009, 3(2): 253-265
[14]  Wang Z, Bovik A C, Sheikh H R, Simoncelli E P. Image quality assessment: from error visibility to structural similarity. IEEE Transactions on Image Processing, 2004, 13(4): 600-612
[15]  Bouazizi I. Estimation of packet loss effects on video quality. In: Proceedings of the 1st International Symposium on Control, Communications and Signal Processing. Hammamet, Tunisia: IEEE, 2004. 91-94
[16]  Babu R V, Bopardikar A S, Perkis A, Hillestad O I. No-reference metrics for video streaming applications. In: the 14th International Packet Video Workshop. California, USA, 2004
[17]  Kanumuri S, Subramanian S G, Cosman P C, Reibman A R. Predicting H.264 packet loss visibility using a generalized linear model. In: Proceedings of the IEEE International Conference on Image Processing. Atlanta, USA: IEEE, 2006. 2245-2248
[18]  Liu T, Wang Y, Boyce J M, Yang H, Wu Z Y. A novel video quality metric for low bit-rate video considering both coding and packet-loss artifacts. IEEE Journal of Selected Topics in Signal Processing, 2009, 3(2): 280-293
[19]  Moorthy A K, Seshadrinathan K, Soundararajan R, Bovik A C. Wireless video quality assessment: a study of subjective scores and objective algorithms. IEEE Transactions on Circuits and Systems for Video Technology, 2010, 20(4): 587-599
[20]  Ninassi A, Le Meur O, Le Callet P, Barbba D. Does where you gaze on an image affect your perception of quality? Applying visual attention to image quality metric. In: Proceedings of the IEEE International Conference on Image Processing. Texas, USA: IEEE, 2007. 169-172
[21]  Radiocommunication Section of ITU, ITU-R Rec. BT500-11: Methodology for the subjective assessment of the quality of television pictures, 2002
[22]  Bernhardt-Walther D. Saliency toolbox [Online], available: http://www.saliencytoolbox.net/, January 2,2010
[23]  Fraunhofer Heinrich Hertz Institute, JM software 10.0 [Online], available: http://iphome.hhi.de/suehring/ tml/download/, September 28, 2011
[24]  Winkler S. Digital Video Quality: Vision Models and Metrics. Chichester: John Wiley and Sons, 2005. 117-120
[25]  Zink M, Kunzel O, Schmitt J, Steinmets R. Subjective impression of variations in layer encoded videos. Lecture Notes in Computer Science. Berlin: Springer, 2003. 137-154
[26]  Pinson M H, Wolf S. A new standardized method for objectively measuring video quality. IEEE Transactions on Broadcasting, 2004, 50(3): 312-322

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