Abstract
This paper proposes a new approach called region mosaicing on contrast pyramids for multi-focus image fusion. A density-based region growing is developed to construct a focused region mask for multi-focus images. The segmented focused region mask is decomposed into a mask pyramid, which is then used for supervised region mosaicing on a contrast pyramid. In this way, the focus measurement and the continuity of focused regions are incorporated and the pixel level pyramid fusion is improved at the region level. Objective and subjective experiments show that the proposed region mosaicing on contrast pyramids approach is more robust to noise and can fully preserves the focus information of the multi-focus images, reducing distortions of the fused images.
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Acknowledgement
This work is supported by the National Science Foundation of China with Nos. 61501132, 61202455, 61472096, the Fundamental Research Funds for the Central Universities with No. HEUCFD1508, and the Heilongjiang Postdoctoral Sustentation Fund with No. LBH-Z14055, the National Science Foundation of Heilongjiang with No. F2016009
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Zhang, L., Sun, J., Feng, W., Lin, J., Yang, Q. (2016). Multi-focus Image Fusion via Region Mosaicing on Contrast Pyramids. In: Yang, Q., Yu, W., Challal, Y. (eds) Wireless Algorithms, Systems, and Applications. WASA 2016. Lecture Notes in Computer Science(), vol 9798. Springer, Cham. https://doi.org/10.1007/978-3-319-42836-9_8
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DOI: https://doi.org/10.1007/978-3-319-42836-9_8
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