Multi-focus images fusion based on block optimization using artificial fish-swarm algorithm

The fixed block size of source images will result in blocking artifacts, fuzzy edge and focus error in multi-focus image fusion. To solve this problem, a new multi-focus image fusion algorithm based on block optimization using artificial fish-swarm is proposed. Firstly, the source images are decomposed into non-overlapping blocks and the sharper blocks are selected using a sharpness criterion. The selected blocks are combined to construct the initial fused image. Then, an improved artificial fish-swarm algorithm is used to optimize the block size according to a fitness function. The final fused image is obtained based on the best block size. Experimental results show that the proposed fusion method has a good quantitative evaluation and visual effect compared to other traditional methods.