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Multi-focus image fusion through pixel-wise voting and morphology

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Abstract

Multi-focus image fusion (MFIf) aims to fuse two or more images into one image, so that the fused image contains more information. This paper proposes a new multi-focus image fusion based on pixel-wise voting and morphology. Firstly, we perform sliding window on the multi-focus image and calculate the gray-scale variance of each sliding window. Then, the voting matrix of each pixel is obtained by comparing the sliding window gray-scale variance. Next, a multi-focus decision map (IFM) is obtained through voting. At the same time, morphological operations can further denoise the IFM and achieve a better image fusion effect. Finally, we also use the weighting method for boundary optimization to get the better fused image. We conducted experiments on ”books”, ”flower”, ”newspaper”, ”lytro” and ”aymaz” datasets. Comparing with other 10 fusion algorithms, the experimental results demonstrate that our proposed multi-focus image fusion method can achieve a good fusion effect.

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Acknowledgements

Thanks to the editor and anonymous review, and to the person who provided the image datasets. This work was supported by Macau University of Science and Technology Foundation (No. FRG-21-020-FI).

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Authors and Affiliations

  1. Faculty of Information Technology, Macau University of Science and Technology, Taipa, 999078, Macau, China

    Huibin Luo, KinTak U & Weikang Zhao

  2. Beijing Institute of Technology, Zhuhai, China

    Huibin Luo

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  1. Huibin Luo
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  2. KinTak U
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  3. Weikang Zhao
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Correspondence to Huibin Luo.

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Luo, H., U, K. & Zhao, W. Multi-focus image fusion through pixel-wise voting and morphology. Multimed Tools Appl 82, 899–925 (2023). https://doi.org/10.1007/s11042-022-13218-y

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