Name
Abstract | ||
|---|---|---|
This paper presented a new image fusion based on compressed sensing (CS). The method decomposes two or more original images using directionlet transform, gets the sparse matrix by the directionlet coefficient sparse representation, and fuses the sparse matrices with the coefficient absolute value maximum scheme. The compressed sample can be obtained through random observation. The fused image is recovered from the reduced samples by solving the optimization. The study demonstrates that the compressive sensing image fusion algorithm based on directionlets has a number of perceived advantages. The simulations show that the proposed algorithm has the advantages of simple structure and easy implementation and also can achieve a better fusion performance. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1186/1687-1499-2014-19 | EURASIP J. Wireless Comm. and Networking |
Keywords | Field | DocType |
Image fusion, Compressive sensing, Directionlet transform | Image fusion,Computer science,Fusion,Real-time computing,Artificial intelligence,Fuse (electrical),Sparse matrix,Compressed sensing,Computer vision,Absolute value,Sparse approximation,Algorithm,Image fusion algorithm | Journal |
Volume | Issue | ISSN |
2014 | 1 | 1687-1499 |
Citations | PageRank | References |
4 | 0.47 | 6 |
Authors | ||
3 | ||