Name
Abstract | ||
|---|---|---|
Video coding has been widely adopted to achieve pleasant video quality at constrained bitrate. In this paper, adaptive frequency coefficient suppression directed by Human Visual System (HVS) is presented for H.264 video coding. Firstly, starting from Just Noticeable Distortion (JND) models for the classic DCT domain, we deduce a JND threshold for the H.264 transform domain with decent adaptation. Then the resultant threshold is used to adaptively suppress the transform coefficients of prediction residuals. It should be noted that our scheme is fully compatible with the H.264 standard. And experimental results show that compared to normal methods, significant bitrate reduction can be obtained by our scheme at similar subjective quality. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ISCAS.2010.5537392 | ISCAS |
Keywords | Field | DocType |
bitrate reduction,video quality,human visual system,just noticeable distortion models,h.264 transform domain,data compression,adaptive frequency coefficient suppression,discrete cosine transforms,h.264-avc video coding,video coding,dct domain,quantization | Computer science,Human visual system model,Control theory,Discrete cosine transform,Coding (social sciences),Artificial intelligence,Video quality,Just noticeable distortion,Computer vision,Image coding,Algorithm,Data compression,Quantization (signal processing) | Conference |
ISSN | ISBN | Citations |
0271-4302 | 978-1-4244-5309-2 | 1 |
PageRank | References | Authors |
0.35 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhengyi Luo | 1 | 35 | 7.85 |
| Li Song | 2 | 323 | 65.87 |
| Shibao Zheng | 3 | 214 | 30.64 |