Name
Abstract | ||
|---|---|---|
In this paper, a novel approach is proposed to remove the motion blur from a video, which is degraded and distorted by fast camera motion. Our approach is based on the image statistics rather than the traditional motion estimation. The image statistics has been successfully applied for blind motion deblurring for a single image by Fergus et al [3] and Levin [10]. Here a three-stage method is used to deal with the video. First, the "unblurred" frames in the video can be found based on the image statistics. Then the blur functions can be obtained by comparing the blurred frames with the unblurred ones. Finally a standard deconvolution algorithm is used to reconstruct the video. Our experiments show that our algorithms are efficient. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1007/978-3-540-76390-1_6 | ACCV |
Keywords | Field | DocType |
novel approach,traditional motion estimation,standard deconvolution algorithm,image statistic,three-stage method,three-stage motion,blur function,single image,blind motion,fast camera motion,motion blur,motion estimation | Computer vision,Block-matching algorithm,Quarter-pixel motion,Pattern recognition,Deblurring,Computer science,Motion compensation,Motion blur,Artificial intelligence,Motion interpolation,Motion estimation,Image restoration | Conference |
Volume | ISSN | ISBN |
4844 | 0302-9743 | 3-540-76389-9 |
Citations | PageRank | References |
1 | 0.35 | 11 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chunjian Ren | 1 | 1 | 0.68 |
| Wenbin Chen | 2 | 57 | 7.88 |
| I-Fan Shen | 3 | 173 | 12.32 |