Multi-source image fusion algorithm based on cellular neural networks with genetic algorithm

作者：Li, Jiangyang; Peng, Zhenming^*

来源：Optik, 2015, 126(24): 5230-5236.

DOI：10.1016/j.ijleo.2015.09.187

• Cellular neural networks
• Genetic algorithms
• Model parameter optimization
• Multi-source image fusion

Multi-source image fusion is a technology that can make a single image to include more information by fusing two or more source images which are obtained by different sensors from the same scene. How to keep the detail and edge information of the original images is the key to multi-source image fusion. To address this problem, we propose a new approach which base on cellular neural networks and genetic algorithms. In this approach, the source images are inputted to the work which has determined the parameters using genetic algorithms and then we can get the fused image. Compared with other fusion algorithms, the proposed approach could fuse multi-source images adaptively and maintain the edges and details information effectively.

• 出版日期2015
• 单位电子科技大学