Abstract
In this paper, we propose a hybrid NR video quality metric with decodable payload. Although NR video quality metric has a strong need from the industry, developing these metrics has been a challenging task. Recently, hybrid models that use both processed video sequences and bit-stream data have shown promising results. In particular, from bitstream data, useful information can be extracted for video quality estimation, which includes codec information and impairment due to transmission errors. In the proposed method, we used packet information from the bit-stream data and estimated transmission impairment by decoding the payload to estimate the video quality. The proposed method was tested for the H.264 standard and it showed promising results. Also, the proposed method was independently evaluated using large datasets and it produced good performance.
| Original language | English |
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| Title of host publication | IISA 2021 - 12th International Conference on Information, Intelligence, Systems and Applications |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| ISBN (Electronic) | 9781665400329 |
| DOIs | |
| Publication status | Published - 2021 Jul 12 |
| Event | 12th International Conference on Information, Intelligence, Systems and Applications, IISA 2021 - Virtual, Chania Crete, Greece Duration: 2021 Jul 12 → 2021 Jul 14 |
Publication series
| Name | IISA 2021 - 12th International Conference on Information, Intelligence, Systems and Applications |
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Conference
| Conference | 12th International Conference on Information, Intelligence, Systems and Applications, IISA 2021 |
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| Country/Territory | Greece |
| City | Virtual, Chania Crete |
| Period | 21/7/12 → 21/7/14 |
Bibliographical note
Publisher Copyright:© 2021 IEEE.
All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Computer Science Applications
- Information Systems
- Information Systems and Management