Name
Title | ||
|---|---|---|
Segmentation-based spatially adaptive motion blur removal and its application to surveillance systems. |
Abstract | ||
|---|---|---|
Various image restoration methods have been studied for removing space-variant motion blur such as iterative and POCS method. However, their computational complexity of the methods, such as regularized iteration and POCS method, is so high that they can hardly be implemented in real-time. In this paper, we address the method to reduce the compu- tational complexity by selecting the region to be restored. The primary application area of the proposed method is a surveillance system which requires accurate object extrac- tion, identification, and tracking functions. To remove mo- tion blur, we propose a new spatially adaptive regularized iterative image restoration algorithm. Experimental results show the the proposed algorithm can efficiently remove space- variant motion blur with significantly reduced computational overhead. |
Year | DOI | Venue |
|---|---|---|
2001 | 10.1109/ICIP.2001.958999 | ICIP (1) |
Keywords | Field | DocType |
object tracking,iterative methods,image segmentation,object recognition,tracking,degradation,iterative algorithm,computational complexity,image restoration,real time,application software,adaptive signal processing | Computer vision,Object detection,Pattern recognition,Iterative method,Computer science,Motion blur,Image segmentation,Video tracking,Artificial intelligence,Adaptive filter,Image restoration,Computational complexity theory | Conference |
Volume | ISSN | ISBN |
1 | 1522-4880 | 0-7803-6725-1 |
Citations | PageRank | References |
8 | 0.78 | 3 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sang-Kyu Kang | 1 | 142 | 12.20 |
| Jihong Min | 2 | 19 | 3.73 |
| Joon Ki Paik | 3 | 129 | 18.73 |