Abstract
For the pulse-coupled neural network (PCNN) has an inherent ability to segment images, we present a multisensor image fusion scheme based on PCNN in this paper. The algorithm adopts salience and visibility as two extracted features for each segmented region to determine the fusion weight. Extensive experimental results have demonstrated that the proposed method has extensive application scope and it outperforms the discrete wavelet transform approach, both in visual effect and objective evaluation criteria, particularly when there is movement in the objects or mis-registration of the source images.
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© 2005 Springer-Verlag Berlin Heidelberg
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Li, M., Cai, W., Tan, Z. (2005). Pulse Coupled Neural Network Based Image Fusion. In: Wang, J., Liao, XF., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3497. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427445_119
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DOI: https://doi.org/10.1007/11427445_119
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25913-8
Online ISBN: 978-3-540-32067-8
eBook Packages: Computer ScienceComputer Science (R0)