Abstract
Based on image contents, the better to simulate the process pattern of human eyes vision, a fusion algorithm of integration and highlight for the image details is proposed. Through wavelet transform, a regional cross entropy fusion rule is used for the low-frequency component which reflects approximate content, and a region brightness details priority weighted fusion rule is used for the high-frequency component which reflects detail features of image. Finally, the fusion image is reconstructed through an inverse transform of wavelet. Experimental results show that by using this algorithm, the mutual information between the images can be fused organically, the image clarity is raised, the fusion image details and brightness information are enhanced. Strong support for the follow-up information analysis and extractive ability of the images are provided.
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© 2012 Springer-Verlag Berlin Heidelberg
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Ge, W., Li, P., Xu, J.L. (2012). Multi-resolution Image Fusion Algorithm Based on Regional Cross Entropy and Regional Priority. In: Lei, J., Wang, F.L., Deng, H., Miao, D. (eds) Artificial Intelligence and Computational Intelligence. AICI 2012. Lecture Notes in Computer Science(), vol 7530. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33478-8_54
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DOI: https://doi.org/10.1007/978-3-642-33478-8_54
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33477-1
Online ISBN: 978-3-642-33478-8
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