Abstract
Aiming at solving the problem of multi-focus image fusion, this paper proposes a visible-light images fusion method which is based on grey relation of similarity in Contourlet domain. Firstly, the source images are decomposed by multi-scale Contourlet transform, then the high-frequency coefficients of each fused image are divided into small blocks. The different fusion strategies of high-frequency coefficients are formulated based on the similarities of these sub-blocks which are determined by the Grey Euclid Relational Degrees of grey theory, while the low-frequency coefficients are fused by arithmetic mean method; Finally, the fused image is reconstructed by the inverse Contourlet transform. The experimental results show that the proposed method is superior to pyramid-based methods and wavelet-transform-based methods in terms of information entropy, standard deviation and definition.
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Jiao, L., Deng, J., Zhang, L., Lin, Q. (2021). Multi-focus Image Fusion Algorithm Based on Grey Relation of Similarity in Contourlet Domain. In: Barolli, L., Woungang, I., Enokido, T. (eds) Advanced Information Networking and Applications. AINA 2021. Lecture Notes in Networks and Systems, vol 227. Springer, Cham. https://doi.org/10.1007/978-3-030-75078-7_29
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DOI: https://doi.org/10.1007/978-3-030-75078-7_29
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