Abstract
The obtained video sequence scores are statistically averaged as the final quality assessment, and the resulting quality assessment results are less accurate. Therefore, a multimedia video communication quality assessment system platform based NS2 is designed. On the basis of compressed sensing theory, image/video signal is the main research object, aiming at the requirements of quality assessment methods in video transmission systems and the determination of observations in transmission, a video signal recovery quality based on redundant observations is proposed. The purpose of the evaluation method is to solve the problem of quality estimation after video recovery for non-structural dimensionality reduction signals in the transmission of video observations. According to the obtained video quality information, an adaptive adjustment scheme of quality information feedback observation rate suitable for video transmission system is designed to solve the problem of determining the observing rate of unknown sparse signal and improve the quality of video recovery. Under the scheme of observation rate adaptive adjustment, the quality assessment model is given considering the requirements of compressive sensing video features and the subjective perceived quality characteristics in the video system. Meanwhile, a video transmission quality evaluation platform is built based on the evaluation model. The experimental results show that the minimum root mean square error of the proposed method is 0.08. The mean square error of traditional methods are much higher than the proposed method, indicating that the proposed method can better simulate the subjective feelings of the human eye, and the obtained quality assessment results are more accurate.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Abdel-Basset M, Mohamed M, Sangaiah AK (2018) Neutrosophic AHP-Delphi Group decision making model based on trapezoidal neutrosophic numbers. J Ambient Intell Humaniz Comput 9(5):1427–1443
Ali R, Pal AK, Kumari S, Sangaiah AK, Li X, Wu FJ (2018) An enhanced three factor based authentication protocol using wireless medical sensor networks for healthcare monitoring. J Ambient Intell Humaniz Comput. https://doi.org/10.1007/s12652-018-1015-9 (first online)
Al-Naji A, Lee SH, Chahl J (2017) Quality index evaluation of videos based on fuzzy interface system. IET Image Process 11(5):292–300. https://doi.org/10.1049/iet-ipr.2016.0569
Che HL, Yu M, Chen F, Peng Z (2016) Spatio-temporal structural-based stereoscopic video quality metric. Opto Electron Eng 43(11):82–87. https://doi.org/10.3969/j.issn.1003-501X.2016.11.013
Chen YS, Chuang HM, Sangaiah AK, Lin CK, Huang WB (2018) A study for project risk management using an advanced MCDM-based DEMATEL-ANP approach. J Ambient Intell Humaniz Comput. https://doi.org/10.1007/s12652-018-0973-2 (first online)
Dubey H, Kumaresan R, Mankodiya K (2018) Harmonic sum-based method for heart rate estimation using ppg signals affected with motion artifacts. J Ambient Intell Humaniz Comput 9(1):137–150. https://doi.org/10.1007/s12652-016-0422-z
Formato A, Ianniello D, Villecco F, Lenza TLL, Guida D (2017) Design optimization of the plough working surface by computerized mathematical model. Emir J Food Agric 29(1):36–44. https://doi.org/10.9755/ejfa.2015-10-918
Gaocheng L, Shuai L, Muhammad K, Sangaiah AK, Doctor F (2018) Object tracking in vary lighting conditions for fog based intelligent surveillance of public spaces. IEEE Access 6:29283–29296. https://doi.org/10.1109/ACCESS.2018.2834916
Kourtis MA, Koumaras H, **louris G, Liberal F (2017) An NFV-based video quality assessment method over 5 G small cell networks. IEEE Multimed 24(4):68–78. https://doi.org/10.1109/MMUL.2017.265091534
Larson M, Soleymani M, Gravier G, Ionescu B, Jones GJF (2017) The benchmarking initiative for multimedia evaluation: MediaEval 2016. IEEE Multimed 24(1):93–96. https://doi.org/10.1109/MMUL.2017.9
Lin Y, Wang C, Wang JX, Dou Z (2016) A novel dynamic spectrum access framework based on reinforcement learning for cognitive radio sensor networks. Sensors BASEL 16(10):1675. https://doi.org/10.3390/s16101675
Liu S, Cheng X, LAN C, Fu W, Li Q, Zhou J (2013) Fractal property of generalized M-set with rational number exponent. Appl Math Comput 220:668–675. https://doi.org/10.1016/j.amc.2013.06.096
Liu S, Cheng X, Fu W, Zhou Y, Li Q (2014) Numeric characteristics of generalized M-set with its asymptote. Appl Math Comput 243:767–774. https://doi.org/10.1016/j.amc.2014.06.016
Liu S, Fu W, He L, Zhou J, Ma M (2017) Distribution of primary additional errors in fractal encoding method. Multimed Tools Appl 76(4):5787–5802. https://doi.org/10.1007/s11042-014-2408-1
Meixner B (2017) A pattern-based evaluation of download and cache management algorithms for annotated interactive non-linear videos. Multimed Syst 23(5):527–561. https://doi.org/10.1007/s00530-016-0512-y
Ni H, Cho S, Mankoff J, Yang J (2018) Automated recognition of hypertension through overnight continuous HRV monitoring. J Ambient Intell Humaniz Comput 9(6):2011–2023. https://doi.org/10.1007/s12652-017-0471-y
Pan Z, Liu S, Fu W (2017) A review of visual moving target tracking. Multimed Tools Appl 76(16):16989–17018. https://doi.org/10.1007/s11042-016-3647-0
Phapatanaburi K, Wang L, Oo Z, Li W, Nakagawa S, Iwahashi M (2017) Noise robust voice activity detection using joint phase and magnitude based feature enhancement. J Ambient Intell Humaniz Comput 8(6):845–859. https://doi.org/10.1007/s12652-017-0482-8
Sena P, D’Amore M, Pappalardo M, Pellegrino A, Fiorentino A, Villecco F (2013) Studying the influence of cognitive load on driver’s performances by a fuzzy analysis of lane kee** in a drive simulation. IFAC Proc Vol 46(21):151–156. https://doi.org/10.3182/20130904-4-JP-2042.00167
Sharma D, Bhondekar AP, Shukla AK, Ghanshyam C (2016) A review on technological advancements in crowd management. J Ambient Intell Humaniz Comput 9(3):485–495. https://doi.org/10.1007/s12652-016-0432-x
Shuai L, Weiling B, Gaocheng L, Wenhui L, Hari S (2018a) Parallel fractal compression method for big video data. Complexity 2018: 2016976. https://doi.org/10.1155/2018/2016976
Shuai L, Gaocheng L, Huiyu Z (2018b) A robust parallel object tracking method for illumination variations. Mobile Netw Appl. https://doi.org/10.1007/s11036-018-1134-8 (first online)
Yang TH, Wu CH, Huang KY, Su MH (2017) Coupled HMM-based multimodal fusion for mood disorder detection through elicited audio–visual signals. J Ambient Intell Humaniz Comput 8(6):895–906. https://doi.org/10.1007/s12652-016-0395-y
Zheng P, Shuai L, Sangaiah AK, Muhammad K (2018) Visual attention feature (VAF): a novel strategy for visual tracking based on cloud platform in intelligent surveillance systems. J Parallel Distrib Comput 120:182–194. https://doi.org/10.1016/j.jpdc.2018.06.012
Acknowledgements
This research is fund by South of the Five Ridges Normal University Humanities and social sciences research project “BYOD environment teaching reform research in secondary schools” with id ZW1806.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Yu, Gh., Xu, J. & Cheng, X. Platform of quality evaluation system for multimedia video communication based NS2. J Ambient Intell Human Comput (2018). https://doi.org/10.1007/s12652-018-1164-x
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s12652-018-1164-x