Name
Abstract | ||
|---|---|---|
In this paper, an efficient approximate sparse representation (SR) algorithm with multi-selection strategy is used to solve the image fusion problem. We have shown that the approximate SR is effective for image fusion even if the sparse coefficients are not the sparsest ones possible. A multi-selection strategy is used to accelerate the process of generating the approximate sparse coefficients which are used to guide the fusion of image patches. The relative parameters are also investigated experimentally to further reduce the computational time. The proposed method is compared with some state-of-the-art image fusion approaches on several pairs of multi-source images. The experimental results exhibit that the proposed method is able to yield superior fusion results with less consumption time. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1142/S0219691316500247 | INTERNATIONAL JOURNAL OF WAVELETS MULTIRESOLUTION AND INFORMATION PROCESSING |
Keywords | Field | DocType |
Sparse representation, image fusion, multi-resolution, multi-modal sensors | Mathematical optimization,Pattern recognition,Image fusion,Computer science,Sparse approximation,Fusion,Artificial intelligence | Journal |
Volume | Issue | ISSN |
14 | 4 | 0219-6913 |
Citations | PageRank | References |
4 | 0.44 | 11 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bin Yang | 1 | 27 | 6.06 |
| Yang Chao | 2 | 4 | 0.44 |
| Huang Guoyu | 3 | 4 | 0.44 |