You are in:Home/Publications/Optimal multi‐scale geometric fusion based on non‐subsampled contourlet transform and modified central force optimization | |
Dr. Wael Abdel-Rahman Mohamed Ahmed :: Publications: |
Title: | Optimal multi‐scale geometric fusion based on non‐subsampled contourlet transform and modified central force optimization |
Authors: | El‐Hoseny, Heba M; El‐Rahman, Wael Abd; El‐Shafai, Walid; El‐Rabaie, El‐Sayed M; Mahmoud, Korany R; Abd El‐Samie, Fathi E; Faragallah, Osama S; |
Year: | 2019 |
Keywords: | Not Available |
Journal: | International Journal of Imaging Systems and Technology |
Volume: | 29 |
Issue: | 1 |
Pages: | Not Available |
Publisher: | John Wiley & Sons, Inc. Hoboken, USA |
Local/International: | International |
Paper Link: | Not Available |
Full paper | Not Available |
Supplementary materials | Not Available |
Abstract: |
In the current era of technological development, medical imaging plays an important part in several applications of medical diagnosis and therapy. This requires more precise images with much more details and information for correct medical diagnosis and therapy. Medical image fusion is one of the solutions for obtaining much spatial and spectral information in a single image. This article presents an optimization‐based contourlet image fusion approach in addition to a comparative study for the performance of both multi‐resolution and multi‐scale geometric effects on fusion quality. An optimized multi‐scale fusion technique based on the Non‐Subsampled Contourlet Transform (NSCT) using the Modified Central Force Optimization (MCFO) and local contrast enhancement techniques is presented. The first step in the proposed fusion approach is the histogram matching of one of the images to the other |