| Título: | Multi-focus Image Fusion by SML in the Shearlet Subbands |
| Autores: |
Jianhua, Liu; Donghua University Yang, Jianguo; Donghua University Li, Beizhi; Donghua University |
| Fecha: | 2013-07-22 |
| Publicador: | TELKOMNIKA: Indonesian journal of electrical engineering |
| Fuente: |
 |
| Tipo: |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
| Tema: | Shearlet;SML; Image fusion; NSCT |
| Descripción: | It is now widely acknowledged that traditional wavelets are not very effective in dealing with multidimensional signals containing distributed discontinuities. Shearlet Transform is a new discrete multiscale directional representation, which combines the power of multiscale methods with a unique ability to capture the geometry of multidimensional data and is optimally efficient in representing images containing edges. In this work, coefficients with greater Sum-Modified-Laplacian are selected to combine images when high-frequency and low-frequency Shearlet subbands of source images are compared. Numerical experiments demonstrate that the method base on Shearlet Transform and Sum-Modified-Laplacian is very competitive and better than other multi-scale geometric analysis tools in multifocus image fusion both in terms of objectives performance and objective criteria. |
| Idioma: | Inglés |