Comparative Evaluation of VVC, HEVC, H.264, AV1, and VP9 Encoders for Low-Delay Video Applications

Mansri, Islem; Doghmane, Noureddine; Kouadria, Nasreddine; Harize, Saliha; Bekhouch, Amara

doi:10.1109/mcna50957.2020.9264275

Cited by 21 publications

(7 citation statements)

References 8 publications

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“…According to García-Lucas et al [52], AV1 reference encoder does not outperform the HEVC reference encoder in terms of coding eiciency, despite the higher encoding complexity. However, both Mansri et al [94] and Laude et al [81] report AV1 as more eicient than HEVC. Saldanha et al [122] conducted a review on hardware implementations of AV1 and VVC coding tools.…”

Section: Computational Complexity Analysismentioning

confidence: 97%

“…Cerveira et al [26] conducted a similar analysis focusing on memory usage proiling. Multiple studies also included the AV1 codec in their comparisons: [52,81,94]. According to García-Lucas et al [52], AV1 reference encoder does not outperform the HEVC reference encoder in terms of coding eiciency, despite the higher encoding complexity.…”

Section: Computational Complexity Analysismentioning

confidence: 99%

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Image and Video Coding Techniques for Ultra-low Latency

et al. 2022

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The next generation of wireless networks fosters the adoption of latency-critical applications such as XR, connected industry, or autonomous driving. This survey gathers implementation aspects of different image and video coding schemes and discusses their tradeoffs. Standardized video coding technologies such as HEVC or VVC provide a high compression ratio, but their enormous complexity sets the scene for alternative approaches like still image, mezzanine, or texture compression in scenarios with tight resource or latency constraints. Regardless of the coding scheme, we found inter-device memory transfers and the lack of sub-frame coding as limitations of current full-system and software-programmable implementations.

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Section: Computational Complexity Analysismentioning

confidence: 97%

Section: Computational Complexity Analysismentioning

confidence: 99%

Image and Video Coding Techniques for Ultra-low Latency

et al. 2022

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“…Quality assessment differs when it comes to real-time encoding systems. Mansri et al [9] have claimed that each newly developed codec outperforms its predecessor, in terms of coding efficiency, with a consequent increase in computational complexity. It is crucial to find a good trade-off between the encoded video bitrate and encoding time; for example, if a system is designed to operate under good network conditions with expected fast transmission speeds, the bitrate is not crucial, as there is a chance that the encoding time will consume more time than the transmission itself.…”

Section: Related Workmentioning

confidence: 99%

Performance Comparison of H.264 and H.265 Encoders in a 4K FPV Drone Piloting System

et al. 2022

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With the rapid growth of video data traffic on the Internet and the development of new types of video transmission systems, the need for ad hoc video encoders has also increased. One such case involves Unmanned Aerial Vehicles (UAVs), widely known as drones, which are used in drone races, search and rescue efforts, capturing panoramic views, and so on. In this paper, we provide an efficiency comparison of the two most popular video encoders—H.264 and H.265—in a drone piloting system using first-person view (FPV). In this system, a drone is used to capture video, which is then transmitted to FPV goggles in real time. We examine the compression efficiency of 4K drone footage by varying parameters such as Group of Pictures (GOP) size, Quantization Parameter (QP), and target bitrate. The quality of the compressed footage is determined using four objective video quality measures: PSNR, SSIM, VMAF, and BRISQUE. Apart from video quality, encoding time and encoding energy consumption are also compared. The research was performed using numerous nodes on a supercomputer.

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“…On the other hand, both H.264/AVC and H.265/High-Efficiency Video Coding (HEVC) codecs use the same structures to stream and store video. However, the encoding process of HEVC and VP9 is more complex than the H.264/AVC coding standard in terms of execution time, CPU consumption, and hardware implementation [71]. Another good reason of using H.264/AVC is its support for various error-resilience schemes, allowing convenient assessment of their effect in H.264/AVC on QoE and QoS, should the need arise.…”

Section: Limitations and Future Workmentioning

confidence: 99%

VQProtect: Lightweight Visual Quality Protection for Error-Prone Selectively Encrypted Video Streaming

Gillani

Asghar

Shifa

et al. 2022

Entropy

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Mobile multimedia communication requires considerable resources such as bandwidth and efficiency to support Quality-of-Service (QoS) and user Quality-of-Experience (QoE). To increase the available bandwidth, 5G network designers have incorporated Cognitive Radio (CR), which can adjust communication parameters according to the needs of an application. The transmission errors occur in wireless networks, which, without remedial action, will result in degraded video quality. Secure transmission is also a challenge for such channels. Therefore, this paper’s innovative scheme “VQProtect” focuses on the visual quality protection of compressed videos by detecting and correcting channel errors while at the same time maintaining video end-to-end confidentiality so that the content remains unwatchable. For the purpose, a two-round secure process is implemented on selected syntax elements of the compressed H.264/AVC bitstreams. To uphold the visual quality of data affected by channel errors, a computationally efficient Forward Error Correction (FEC) method using Random Linear Block coding (with complexity of O(k(n−1)) is implemented to correct the erroneous data bits, effectively eliminating the need for retransmission. Errors affecting an average of 7–10% of the video data bits were simulated with the Gilbert–Elliot model when experimental results demonstrated that 90% of the resulting channel errors were observed to be recoverable by correctly inferring the values of erroneous bits. The proposed solution’s effectiveness over selectively encrypted and error-prone video has been validated through a range of Video Quality Assessment (VQA) metrics.

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Comparative Evaluation of VVC, HEVC, H.264, AV1, and VP9 Encoders for Low-Delay Video Applications

Cited by 21 publications

References 8 publications

Image and Video Coding Techniques for Ultra-low Latency

Image and Video Coding Techniques for Ultra-low Latency

Performance Comparison of H.264 and H.265 Encoders in a 4K FPV Drone Piloting System

VQProtect: Lightweight Visual Quality Protection for Error-Prone Selectively Encrypted Video Streaming

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