Name
Abstract | ||
|---|---|---|
In this paper, we propose a new image inpainting method based on the property
that much of the image information in the transform domain is sparse. We add a
redundancy to the original image by mapping the transform coefficients with
small amplitudes to zero and the resultant sparsity pattern is used as the side
information in the recovery stage. If the side information is not available,
the receiver has to estimate the sparsity pattern. At the end, the recovery is
done by consecutive projecting between two spatial and transform sets.
Experimental results show that our method works well for both structural and
texture images and outperforms other techniques in objective and subjective
performance measures. |
Year | Venue | Field |
|---|---|---|
2010 | Clinical Orthopaedics and Related Research | Top-hat transform,Computer vision,Pattern recognition,Computer science,Side information,Inpainting,Redundancy (engineering),Artificial intelligence |
DocType | Volume | Citations |
Journal | abs/1011.5 | 0 |
PageRank | References | Authors |
0.34 | 3 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hossein Hosseini | 1 | 96 | 14.52 |
| N. B. Marvasti | 2 | 0 | 0.34 |
| Farrokh Marvasti | 3 | 113 | 13.55 |