Name
Abstract | ||
|---|---|---|
In this paper, we present a new general method for image fusion based on partial differential equation (PDE). We propose to combine pixel-level fusion and diffusion processes through one single powerful equation. The insertion of the relevant information contained in sources is achieved in the fused image by reversing the diffusion process. To solve the well-known instability problem of an inverse diffusion process, we introduce two additional constraints. Then, we propose a general PDE, which integrates one of these constraints as a regularization term. One of the advantages of such an original approach is to improve the quality of the results in case of noisy input images. To answer to the requirements of a 3D specific fusion application, we also propose an extension of the general equation. Finally, few examples and comparisons with classical fusion models will demonstrate the efficiency of our method both on 2D and 3D cases. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/ICIF.2007.4408104 | Quebec, Que. |
Keywords | Field | DocType |
image processing,partial differential equations,diffusion process,image fusion,low-level fusion,partial differential equation,pixel-level fusion,3D application,Image fusion,Partial Differential Equation,anisotropic diffusion | Anisotropic diffusion,Inverse,Computer vision,Diffusion process,Mathematical optimization,Image fusion,Computer science,Image processing,Fusion,Regularization (mathematics),Artificial intelligence,Partial differential equation | Conference |
ISBN | Citations | PageRank |
978-0-662-45804-3 | 4 | 0.42 |
References | Authors | |
12 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sorin Pop | 1 | 27 | 3.02 |
| Olivier Lavialle | 2 | 72 | 9.51 |
| Romulus Terebes | 3 | 49 | 8.42 |
| Monica Borda | 4 | 63 | 13.54 |