Abstract
In this paper we propose an effective color image fusion algorithm based on the simplified pulse coupled neural networks (S-PCNN) and the Laplacian Pyramid algorithm. In the HSV color space, after regional clustering feature of H components by S-PCNN, and then achieved the fusion of the H component from each source image using Oscillation Frequency Graph. At the same time, decomposing S, H component by Laplacian Pyramid algorithm, and then using different fusion rules to fusion S, H component. Finally, inversing HSV transform to get RGB color image. The experiment indicates that the new color image fusion algorithm is more efficient both in the subjective aspect and the objective aspect than other commonly color image fusion algorithm.
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Acknowledgements
Our work is supported by the National Natural Science Foundation of China (No. 61365001, No. 61463052), Natural Science Foundation of Yunnan Province (No. 2012FD003).
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© 2015 Springer International Publishing Switzerland
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Jin, X., Nie, R., Zhou, D., Yu, J. (2015). Color Image Fusion Researching Based on S-PCNN and Laplacian Pyramid. In: Qiang, W., Zheng, X., Hsu, CH. (eds) Cloud Computing and Big Data. CloudCom-Asia 2015. Lecture Notes in Computer Science(), vol 9106. Springer, Cham. https://doi.org/10.1007/978-3-319-28430-9_14
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DOI: https://doi.org/10.1007/978-3-319-28430-9_14
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