Pixel-Level Image Fusion Using Particle Swarm Optimization with Local Search

Pixel-level image fusion is widely used in many fields. We proposed a pixel-level image fusion algorithm based on particle swarm optimization with local search, that is, PSO-LS, which improves performance further. PSO-LS integrated the self-improvement mechanisms from memetic algorithms and can avoid local minimum in PSO. Experiments were carried out on two real world images. It is shown that fusion algorithm based on PSO-LS outperforms that based on PSO, and the former obtained optimal solution rapidly using fewer particles.

[1]  Qingquan Li,et al.  A comparative analysis of image fusion methods , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[2]  Russell C. Eberhart,et al.  A new optimizer using particle swarm theory , 1995, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science.

[3]  Kanti V. Mardia,et al.  Bayesian fused classification of medical images , 1996, IEEE Trans. Medical Imaging.

[4]  Jamie P. Heather,et al.  A review of image fusion technology in 2005 , 2005, SPIE Defense + Commercial Sensing.

[5]  Youcef Chibani.  Multisource image fusion by using the redundant wavelet decomposition , 2003, IGARSS 2003. 2003 IEEE International Geoscience and Remote Sensing Symposium. Proceedings (IEEE Cat. No.03CH37477).

[6]  Peter J. Angeline,et al.  Evolutionary Optimization Versus Particle Swarm Optimization: Philosophy and Performance Differences , 1998, Evolutionary Programming.

[7]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[8]  Mongi A. Abidi,et al.  Data fusion in robotics and machine intelligence , 1992 .

[9]  M. Clerc,et al.  The swarm and the queen: towards a deterministic and adaptive particle swarm optimization , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[10]  Lawrence A. Klein,et al.  Sensor and Data Fusion Concepts and Applications , 1993 .

[11]  David Hooper,et al.  Real-time image fusion: a vision aid for helicopter pilotage , 2002, IS&T/SPIE Electronic Imaging.

[12]  Junying Chen,et al.  Particle Swarm Optimization with Local Search , 2005, 2005 International Conference on Neural Networks and Brain.

[13]  Yue Shi,et al.  A modified particle swarm optimizer , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[14]  杨波,et al.  Review of Pixel-Level Image Fusion , 2010 .

[15]  Zheng Liu,et al.  Experimenting with pixel-level NDT data fusion techniques , 2000, IEEE Trans. Instrum. Meas..

[16]  Rick S. Blum.  Robust image fusion using a statistical signal processing approach , 2005, Inf. Fusion.