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- W4327501277 abstract "Aiming at the problem that the existing multi-focus image fusion algorithms are easy to lose image edge details, a multi-focus image fusion algorithm based on weighted local variance focus detection is proposed. In order to improve the detection accuracy of the focal area in the source image, the gaussian curvature filter is used first to obtain the salient feature map; then the weighted sum of the local variance of the neighboring pixels is calculated as the focus detection value of the central pixel to ensure the detection accuracy of the uniform area of the image; finally generate a decision graph by maximizing the criterion. In order to further improve the spatial consistency of the decision map, a small region removal strategy and guided filters are used to optimize the decision map to obtain the final fused image. The experimental results show that the proposed algorithm can retain the rich detail information of multi-focus images, avoid edge blurring and artifacts caused by fused images, and has better detection ability of focal regions." @default.
- W4327501277 created "2023-03-17" @default.
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- W4327501277 date "2022-09-01" @default.
- W4327501277 modified "2023-09-29" @default.
- W4327501277 title "Multi-focus Image Fusion Algorithm Based on Weighted Local Variance Focus Detection" @default.
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- W4327501277 doi "https://doi.org/10.1109/iccgiv57403.2022.00042" @default.
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