Name
Abstract | ||
|---|---|---|
In this work, we propose the use of sparse signal representation techniques to solve the problem of closed-loop spatial image prediction. The reconstruction of signal in the block to predict is based on basis functions selected with the Matching Pursuit (MP) iterative algorithm, to best match a causal neighborhood. We evaluate this new method in terms of PSNR and bitrate in a H.264 / AVC encoder. Experimental results indicate an improvement of rate-distortion performance. In this paper, we also present results concerning the use of phase correlation to improve the reconstruction trough shifted-basis functions. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1117/12.838911 | VISUAL INFORMATION PROCESSING AND COMMUNICATION |
Keywords | Field | DocType |
Intra-prediction, atomic decomposition, extrapolation, phase correlation | Matching pursuit,Iterative method,Sparse approximation,Signal-to-noise ratio,Algorithm,Basis function,Encoder,Rate–distortion theory,Phase correlation,Physics | Conference |
Volume | ISSN | Citations |
7543 | 0277-786X | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| aurelie martin | 1 | 0 | 0.34 |
| Jean-Jacques Fuchs | 2 | 57 | 15.70 |
| Christine Guillemot | 3 | 1286 | 104.25 |
| dominique thoreau | 4 | 0 | 0.34 |