Name
Abstract | ||
|---|---|---|
We consider the problem of recovering a high-resolution image from a pair consisting of a complete low-resolution image and a high-resolution but incomplete one. We refer to this task as the image zoom completion problem. After discussing possible contexts in which this setting may arise, we introduce a nonlocal regularization strategy, giving full details concerning the numerical optimization of the corresponding energy and discussing its benefits and shortcomings. We also derive two total variation-based algorithms and evaluate the performance of the proposed methods on a set of natural and textured images. We compare the results and get with those obtained with two recent state-of-the-art single-image super-resolution algorithms. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TIP.2016.2571061 | IEEE Trans. Image Processing |
Keywords | DocType | Volume |
Image resolution,Context,Optimization,Image restoration,Convolution,Imaging | Journal | 25 |
Issue | ISSN | Citations |
8 | 1057-7149 | 1 |
PageRank | References | Authors |
0.35 | 33 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Moncef Hidane | 1 | 16 | 3.35 |
| Mireille El Gheche | 2 | 14 | 6.39 |
| Jean-François Aujol | 3 | 1176 | 82.39 |
| Y. Berthoumieu | 4 | 389 | 51.66 |
| Charles-Alban Deledalle | 5 | 387 | 24.00 |