Name
Abstract | ||
|---|---|---|
Among Super-Resolution reconstruction methods, the patch-based computation to find the sparse prior can achieve better reconstruction results. The computing for this method is time-consuming. To overcome this problem, we propose a GPU(Graphic Processing Unit) based algorithm to speed up the process and achieve 7.2 times faster than the original method. We also implement the method of modified LASSO(Least Absolute Shrinkage and Selection Operator) to find sparse priors, which can achieve 13.9 times faster. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.3233/978-1-61499-484-8-1043 | Frontiers in Artificial Intelligence and Applications |
Keywords | Field | DocType |
Super Resolution,LASSO,parallel computing | Computer science,Sparse approximation,Parallel computing,Superresolution | Conference |
Volume | ISSN | Citations |
274 | 0922-6389 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hao-Rong Ding | 1 | 0 | 0.34 |
| Chih-Hung Kuo | 2 | 86 | 14.77 |
| Po-Hung Kuo | 3 | 0 | 0.34 |
| Yan-Tse Chuang | 4 | 0 | 0.34 |