Ultra-High-Definition Video Transmission for Mission-Critical Communication Systems Applications

With the standardization of ultra-high-definition formats and their increasing adoption within the multimedia industry, it has become vital to investigate how such a resolution could impact the quality of experience with respect to mission-critical communication systems. While this standardization enables improved perceptual quality of video content, how it can be used in mission-critical communications remains a challenge, with the main challenge being processing. This chapter discusses the challenges and potential solutions for the deployment of ultra-high-definition video transmission for mission-critical applications. In addition, it examines the state-of-the-art solutions for video processing and explores potential solutions. Finally, the authors predict future research directions in this area.

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Ultra-High-Definition Video Transmission for Mission-Critical Communication Systems Applications

Research Anthology on Recent Trends, Tools, and Implications of Computer Programming ◽

10.4018/978-1-7998-3016-0.ch041 ◽

2021 ◽

pp. 899-915

Author(s):

Anthony Olufemi Tesimi Adeyemi-Ejeye ◽

Geza Koczian ◽

Mohammed Abdulrahman Alreshoodi ◽

Michael C. Parker ◽

Stuart D. Walker

Keyword(s):

Video Processing ◽

Communication Systems ◽

Video Transmission ◽

Perceptual Quality ◽

Future Research ◽

High Definition ◽

High Definition Video ◽

Main Challenge ◽

Mission Critical

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Enhancing perceptual quality of watermarked high-definition video through composite mask

2010 2nd International Conference on Image Processing Theory, Tools and Applications ◽

10.1109/ipta.2010.5586742 ◽

2010 ◽

Author(s):

Tae-Woo Oh ◽

Kyung-Su Kim ◽

Hae-Yeon Lee ◽

Ji-Won Lee ◽

Heung-Kyu Lee

Keyword(s):

Perceptual Quality ◽

High Definition ◽

High Definition Video

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Assessing Quality of Experience for High Definition Video Streaming under Diverse Packet Loss Patterns

Communications in Computer and Information Science - Multimedia Communications, Services and Security ◽

10.1007/978-3-642-21512-4_16 ◽

2011 ◽

pp. 137-143 ◽

Cited By ~ 1

Author(s):

Lucjan Janowski ◽

Piotr Romaniak ◽

Zdzisław Papir

Keyword(s):

Video Streaming ◽

Packet Loss ◽

Quality Of Experience ◽

High Definition ◽

High Definition Video

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Machine Learning-Based Subjective Quality Estimation for Video Streaming Over Wireless Networks

Advances in Wireless Technologies and Telecommunication - Next-Generation Wireless Networks Meet Advanced Machine Learning Applications ◽

10.4018/978-1-5225-7458-3.ch010 ◽

2019 ◽

pp. 235-254

Author(s):

Monalisa Ghosh ◽

Chetna Singhal

Keyword(s):

Machine Learning ◽

Wireless Networks ◽

Video Streaming ◽

Video Transmission ◽

Video Quality ◽

Subjective Quality ◽

Perceptual Quality ◽

Support Vector ◽

Machine Learning Model

Video streaming services top the internet traffic surging forward a competitive environment to impart best quality of experience (QoE) to the users. The standard codecs utilized in video transmission systems eliminate the spatiotemporal redundancies in order to decrease the bandwidth requirement. This may adversely affect the perceptual quality of videos. To rate a video quality both subjective and objective parameters can be used. So, it is essential to construct frameworks which will measure integrity of video just like humans. This chapter focuses on application of machine learning to evaluate the QoE without requiring human efforts with higher accuracy of 86% and 91% employing the linear and support vector regression respectively. Machine learning model is developed to forecast the subjective quality of H.264 videos obtained after streaming through wireless networks from the subjective scores.

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