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• W4385776875 abstract "Shape from focus (SFF) is a technique for reconstructing the 3D shape of a scene from a sequence of multi-focus images. The quality of the shape reconstruction depends on the accuracy of the initial focus volume (FV) and the optimization of the initial depth map. The initial FV is calculated by the focus measure (FM) operator. Traditional FM operators perform poorly in preserving structural edges and weak texture areas. In depth map optimization, strong smoothness constraints are mainly used for improvement, but this relies on the accuracy of the initial depth map. Therefore, in this paper, we propose a complete SFF method framework. We suggest performing detail transformation on the images to enhance texture information, especially in weak texture areas. For micro-images, a curvature method is proposed to evaluate the sharpness level of the images. Noise in the initial depth map is divided into two types and optimized using spatial clustering and static guided filtering methods. Experiments have been conducted to validate the effectiveness of the proposed method using both synthetic and real objects. Compared with existing methods, the proposed method achieves excellent results in accurately reconstructing 3D shapes." @default.
• W4385776875 created "2023-08-12" @default.
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• W4385776875 date "2024-01-01" @default.
• W4385776875 modified "2023-10-17" @default.
• W4385776875 title "A novel algorithm for three-dimensional shape reconstruction for microscopic objects based on shape from focus" @default.
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• W4385776875 doi "https://doi.org/10.1016/j.optlastec.2023.109931" @default.
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