Name
Abstract | ||
|---|---|---|
Reduced reference video quality assessment techniques provide a practical and convenient way of evaluating the quality of a processed video. In this paper, we propose a method to efficiently compress standardized VQM (Video Quality Model) [1] features to bit-rates that are small relative to the transmitted video. This is achieved through two stages of compression. In the first stage, we remove the redundancy in the features by only transmitting the necessary original video features at the lowest acceptable resolution for the calculation of the final VQM value. The second stage involves using the features of the processed video at the receiver as side-information for efficient entropy coding and reconstruction of the original video features. Experimental results demonstrate that our approach achieves high compression ratios of more than 30× with small error in the final VQM values. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/MMSP.2011.6093809 | 2011 IEEE 13th International Workshop on Multimedia Signal Processing |
Keywords | Field | DocType |
VQM features,low bit-rate video quality monitoring,video quality model,entropy coding | Computer vision,Pattern recognition,Computer science,Motion compensation,Multiview Video Coding,Artificial intelligence,Data compression,Video denoising,Video quality,Video compression picture types,Rate–distortion optimization,Scalable Video Coding | Conference |
ISSN | ISBN | Citations |
2163-3517 | 978-1-4577-1432-0 | 2 |
PageRank | References | Authors |
0.65 | 5 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mina Makar | 1 | 93 | 7.27 |
| Yao-chung Lin | 2 | 119 | 11.14 |
| Andre F. de Araújo | 3 | 53 | 6.83 |
| Bernd Girod | 4 | 8988 | 1062.96 |