基于改进快速推进方法的扫描电镜图像形状恢复

Y. Iwahori, Lei Huang, Aili Wang, M. Bhuyan
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引用次数: 0

摘要

快速推进法提供了一种求解Eikonal方程的方法,也可用于求解由阴影生成形状的问题。但它仍然有一些局限性。本文提出了一种利用改进的快速行军法恢复三维形状的新方法。将二阶有限差分、对角线网格点和新的更新方式应用到改进的FMM中,该方法可以恢复兰伯特图像的三维形状。在此基础上,提出了一种利用仿射变换和神经网络学习对扫描电子显微镜(SEM)图像进行强度修正的方法,使改进后的FMM能够从扫描电子显微镜图像中恢复出三维形状。最后,将所提方法与已有方法进行了比较。实验包括数值实验、计算机模拟实验和实像实验。结果表明,该方法具有较好的鲁棒性和准确性。
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Shape Recovery Using Improved Fast Marching Method for SEM Image
Fast Marching method provides a solution to the Eikonal equation, and it also can be used to solve the Shape from Shading problem. But it still has some limitations. This paper proposes a new approach to recover 3-D shape by using improved Fast Marching method. The second-order finite difference, the diagonal grid points, and new update mode is used to improved FMM and the method can recover 3-D shape for Lambert image. Then we propose a method to modify the original Scanning Electron Microscope (SEM) image with intensity modification by using affine transform and NN learning, thus the improved FMM can recover 3-D shape from SEM image. Finally, the results were compared between the proposed method and previous method. Experiment includes numerical experiments, computer simulation experiments and real image. The results show the method is satisfied with Lambert and SEM image, and both robust and accurate.
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