Name
Abstract | ||
|---|---|---|
In this paper, we present a no-reference video quality metric that blindly estimates the quality of a video. The proposed approach makes use of a data hiding technique to embed a fragile mark into perceptually important areas of the video frame. To estimate the importance of an area, we take into account three perceptual features that are known to attract visual attention: motion, contrast, and color. At the receiver, the mark is extracted from the perceptually important areas of the decoded video. Then, a quality measure of the video is obtained by computing the degradation of the extracted mark. Simulation results indicate that the proposed video quality metric outperforms standard Peak Signal to Noise Ratio (PSNR) in estimating the perceived quality of a video. Additionally, results from a subjective experiment show that the metric output values increase monotonically with the mean annoyance scores gathered from the human observers. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/ICIP.2005.1530613 | 2005 INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), VOLS 1-5 |
Keywords | Field | DocType |
decoding,feature extraction,video,peak signal to noise ratio,watermarking,data hiding | Peak signal-to-noise ratio,Computer vision,Digital watermarking,Pattern recognition,Computer science,Information hiding,Subjective video quality,Feature extraction,Artificial intelligence,Decoding methods,Annoyance,Video quality | Conference |
ISSN | Citations | PageRank |
1522-4880 | 8 | 0.70 |
References | Authors | |
6 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Marco Carli | 1 | 252 | 28.85 |
| Mylene Christine Queiroz De Farias | 2 | 53 | 4.36 |
| Elisa Drelie Gelasca | 3 | 154 | 10.55 |
| Roberto Tedesco | 4 | 8 | 0.70 |
| A Neri | 5 | 679 | 72.31 |