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Proceedings Paper

Image fusion algorithm based on energy of Laplacian and PCNN
Author(s): Meili Li; Hongmei Wang; Yanjun Li; Ke Zhang
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Paper Abstract

Owing to the global coupling and pulse synchronization characteristic of pulse coupled neural networks (PCNN), it has been proved to be suitable for image processing and successfully employed in image fusion. However, in almost all the literatures of image processing about PCNN, linking strength of each neuron is assigned the same value which is chosen by experiments. This is not consistent with the human vision system in which the responses to the region with notable features are stronger than that to the region with nonnotable features. It is more reasonable that notable features, rather than the same value, are employed to linking strength of each neuron. As notable feature, energy of Laplacian (EOL) is used to obtain the value of linking strength in PCNN in this paper. Experimental results demonstrate that the proposed algorithm outperforms Laplacian-based, wavelet-based, PCNN -based fusion algorithms.

Paper Details

Date Published: 2 April 2010
PDF: 6 pages
Proc. SPIE 7651, International Conference on Space Information Technology 2009, 76510M (2 April 2010); doi: 10.1117/12.855556
Show Author Affiliations
Meili Li, Northwestern Polytechnical Univ. (China)
Xi'an Shiyou Univ. (China)
Hongmei Wang, Northwestern Polytechnical Univ. (China)
Yanjun Li, Northwestern Polytechnical Univ. (China)
Ke Zhang, Northwestern Polytechnical Univ. (China)

Published in SPIE Proceedings Vol. 7651:
International Conference on Space Information Technology 2009
Xingrui Ma; Baohua Yang; Ming Li, Editor(s)

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