Fuzzy logic inference system‐based hybrid quality prediction model for wireless 4kUHD H.265‐coded video streaming
Networked visual applications such video streaming have grown exponentially in recent years, yet are known to be sensitive to network impairments. However, available measurement techniques that adopt a full reference model are impractical in real‐time streaming because they require the original vide...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2015-11-01
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| Series: | IET Networks |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/iet-net.2015.0018 |
| _version_ | 1818666613850767360 |
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| author | Mohammed Alreshoodi Anthony Olufemi Adeyemi‐Ejeye John Woods Stuart D. Walker |
| author_facet | Mohammed Alreshoodi Anthony Olufemi Adeyemi‐Ejeye John Woods Stuart D. Walker |
| author_sort | Mohammed Alreshoodi |
| collection | DOAJ |
| description | Networked visual applications such video streaming have grown exponentially in recent years, yet are known to be sensitive to network impairments. However, available measurement techniques that adopt a full reference model are impractical in real‐time streaming because they require the original video sequence available at the receivers side. The primary aim of this study is to present a hybrid no‐reference prediction model for the perceptual quality of 4kUHD H.265‐coded video in the wireless domain. The contributions of this paper are two‐fold: first, an investigation of the impact of quality of service (QoS) parameters on 4kUHD H.265‐coded video transmission in an experimental environment; second, objective model based on fuzzy logic inference system is developed to predict the visual quality by mapping QoS parameters to the measured quality of experience. The model is evaluated in contrast to random neural networks. The results show that good prediction accuracy was obtained from the proposed hybrid prediction model. This study will help in the development of a reference‐free video quality prediction model and QoS control methods for 4kUHD video streaming. |
| first_indexed | 2024-12-17T06:07:19Z |
| format | Article |
| id | doaj.art-20e23e2b751e47328929e5bba0ad70b6 |
| institution | Directory Open Access Journal |
| issn | 2047-4954 2047-4962 |
| language | English |
| last_indexed | 2024-12-17T06:07:19Z |
| publishDate | 2015-11-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Networks |
| spelling | doaj.art-20e23e2b751e47328929e5bba0ad70b62022-12-21T22:00:43ZengWileyIET Networks2047-49542047-49622015-11-014629630310.1049/iet-net.2015.0018Fuzzy logic inference system‐based hybrid quality prediction model for wireless 4kUHD H.265‐coded video streamingMohammed Alreshoodi0Anthony Olufemi Adeyemi‐Ejeye1John Woods2Stuart D. Walker3School of Computer Science and Electronic EngineeringUniversity of EssexWivenhoe ParkColchesterCO4 3SQUKSchool of Computer Science and Electronic EngineeringUniversity of EssexWivenhoe ParkColchesterCO4 3SQUKSchool of Computer Science and Electronic EngineeringUniversity of EssexWivenhoe ParkColchesterCO4 3SQUKSchool of Computer Science and Electronic EngineeringUniversity of EssexWivenhoe ParkColchesterCO4 3SQUKNetworked visual applications such video streaming have grown exponentially in recent years, yet are known to be sensitive to network impairments. However, available measurement techniques that adopt a full reference model are impractical in real‐time streaming because they require the original video sequence available at the receivers side. The primary aim of this study is to present a hybrid no‐reference prediction model for the perceptual quality of 4kUHD H.265‐coded video in the wireless domain. The contributions of this paper are two‐fold: first, an investigation of the impact of quality of service (QoS) parameters on 4kUHD H.265‐coded video transmission in an experimental environment; second, objective model based on fuzzy logic inference system is developed to predict the visual quality by mapping QoS parameters to the measured quality of experience. The model is evaluated in contrast to random neural networks. The results show that good prediction accuracy was obtained from the proposed hybrid prediction model. This study will help in the development of a reference‐free video quality prediction model and QoS control methods for 4kUHD video streaming.https://doi.org/10.1049/iet-net.2015.0018fuzzy logic inference system‐based hybrid quality prediction modelwireless 4kUHD H.265‐coded video streamingmeasurement techniquesfull reference modelvideo sequencehybrid no‐reference prediction model |
| spellingShingle | Mohammed Alreshoodi Anthony Olufemi Adeyemi‐Ejeye John Woods Stuart D. Walker Fuzzy logic inference system‐based hybrid quality prediction model for wireless 4kUHD H.265‐coded video streaming IET Networks fuzzy logic inference system‐based hybrid quality prediction model wireless 4kUHD H.265‐coded video streaming measurement techniques full reference model video sequence hybrid no‐reference prediction model |
| title | Fuzzy logic inference system‐based hybrid quality prediction model for wireless 4kUHD H.265‐coded video streaming |
| title_full | Fuzzy logic inference system‐based hybrid quality prediction model for wireless 4kUHD H.265‐coded video streaming |
| title_fullStr | Fuzzy logic inference system‐based hybrid quality prediction model for wireless 4kUHD H.265‐coded video streaming |
| title_full_unstemmed | Fuzzy logic inference system‐based hybrid quality prediction model for wireless 4kUHD H.265‐coded video streaming |
| title_short | Fuzzy logic inference system‐based hybrid quality prediction model for wireless 4kUHD H.265‐coded video streaming |
| title_sort | fuzzy logic inference system based hybrid quality prediction model for wireless 4kuhd h 265 coded video streaming |
| topic | fuzzy logic inference system‐based hybrid quality prediction model wireless 4kUHD H.265‐coded video streaming measurement techniques full reference model video sequence hybrid no‐reference prediction model |
| url | https://doi.org/10.1049/iet-net.2015.0018 |
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