Name
Abstract | ||
|---|---|---|
We propose a simple non-linear content-adaptive filter that is efficient in removing noise from a video. The proposed filter is called spatiotemporal varying filter (STVF) and is able to produce optimal results in the sense that it minimizes the weighted least square error. STVF combines the advantages of conventional denoising filters that enable it to decrease the noise variance in smooth areas but at the same time retains the sharpness of edges in object boundaries. Simulation results show that STVF outperforms the conventional denoising methods like low-pass filtering, median filtering and Wiener filtering. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/ICASSP.2005.1415488 | ICASSP (2) |
Keywords | Field | DocType |
entropy,low pass filter,median filter,impulse noise,adaptive filters,wiener filtering,median filtering,videoconference,kalman filters,minimisation,noise reduction,video compression,low pass filters,nonlinear filter,wiener filter | Wiener filter,Computer vision,Root-raised-cosine filter,Median filter,Computer science,Non-local means,Artificial intelligence,Adaptive filter,Nonlinear filter,Video denoising,Filter design | Conference |
Volume | ISSN | ISBN |
2 | 1520-6149 | 0-7803-8874-7 |
Citations | PageRank | References |
4 | 0.48 | 2 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tai-wai Chan | 1 | 22 | 3.62 |
| Oscar C. Au | 2 | 1592 | 176.54 |
| Tak-song Chong | 3 | 13 | 2.61 |
| Wing-san Chau | 4 | 16 | 3.24 |