QoE-Based Performance Comparison of AVC, HEVC, and VP9 on Mobile Devices with Additional Influencing Factors

Author:

Nawaz Omer1,Fiedler Markus1ORCID,Khatibi Siamak1ORCID

Affiliation:

1. Department of Technology and Aesthetics, Blekinge Tekniska Högskola, 37179 Karlskrona, Sweden

Abstract

While current video quality assessment research predominantly revolves around resolutions of 4 K and beyond, targeted at ultra high-definition (UHD) displays, effective video quality for mobile video streaming remains primarily within the range of 480 p to 1080 p. In this study, we conducted a comparative analysis of the quality of experience (QoE) for widely implemented video codecs on mobile devices, specifically Advanced Video Coding (AVC), its successor High-Efficiency Video Coding (HEVC), and Google’s VP9. Our choice of 720 p video sequences from a newly developed database, all with identical bitrates, aimed to maintain a manageable subjective assessment duration, capped at 35–40 min. To mimic real-time network conditions, we generated stimuli by streaming original video clips over a controlled emulated setup, subjecting them to eight different packet-loss scenarios. We evaluated the quality and structural similarity of the distorted video clips using objective metrics, including the Video Quality Metric (VQM), Peak Signal-to-Noise Ratio (PSNR), Video Multi-Method Assessment Fusion (VMAF), and Multi-Scale Structural Similarity Index (MS-SSIM). Subsequently, we collected subjective ratings through a custom mobile application developed for Android devices. Our findings revealed that VMAF accurately represented the degradation in video quality compared to other metrics. Moreover, in most cases, HEVC exhibited an advantage over both AVC and VP9 under low packet-loss scenarios. However, it is noteworthy that in our test cases, AVC outperformed HEVC and VP9 in scenarios with high packet loss, based on both subjective and objective assessments. Our observations further indicate that user preferences for the presented content contributed to video quality ratings, emphasizing the importance of additional factors that influence the perceived video quality of end users.

Publisher

MDPI AG

Reference64 articles.

1. (2023, February 01). Cisco Annual Internet Report-Cisco Annual Internet Report (2018–2023) White Paper. Available online: https://www.cisco.com/c/en/us/solutions/collateral/executive-perspectives/annual-internet-report/white-paper-c11-741490.html.

2. (2023, January 21). Ericsson Mobility Report November 2022. Available online: https://www.ericsson.com/en/reports-and-papers/mobility-report/reports/november-2022.

3. (2023, September 16). Precedence Research: Mobile Gaming Market Size. Available online: https://www.precedenceresearch.com/mobile-gaming-market.

4. (2023, September 13). Most Used Devices for Digital Videos in the U.S.. Available online: https://www.statista.com/forecasts/997109/most-used-devices-for-digital-videos-in-the-us.

5. (2023, September 13). World Telecommunication/ICT Indicators Database. Available online: https://www.itu.int:443/en/ITU-D/Statistics/Pages/publications/wtid.aspx.

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