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Mathematical Problems in Engineering
Volume 2015, Article ID 340675, 14 pages
Research Article

Multifocus Image Fusion Using Biogeography-Based Optimization

1School of Optoelectronic Information, University of Electronic Science and Technology of China, Chengdu 611731, China
2School of Computer Science & Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China
3School of Engineering, Brown University, Providence, RI 02912, USA

Received 11 October 2014; Revised 4 February 2015; Accepted 7 February 2015

Academic Editor: George S. Dulikravich

Copyright © 2015 Ping Zhang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


For multifocus image fusion in spatial domain, sharper blocks from different source images are selected to fuse a new image. Block size significantly affects the fusion results and a fixed block size is not applicable in various multifocus images. In this paper, a novel multifocus image fusion algorithm using biogeography-based optimization is proposed to obtain the optimal block size. The sharper blocks of each source image are first selected by sum modified Laplacian and morphological filter to contain an initial fused image. Then, the proposed algorithm uses the migration and mutation operation of biogeography-based optimization to search the optimal block size according to the fitness function in respect of spatial frequency. The chaotic search is adopted during iteration to improve optimization precision. The final fused image is constructed based on the optimal block size. Experimental results demonstrate that the proposed algorithm has good quantitative and visual evaluations.