可视化
扫描电子显微镜
材料科学
计算机科学
特征(语言学)
电导率
人工智能
计算机视觉
微观结构
光学
物理
复合材料
语言学
量子力学
哲学
作者
Shuiquan Pang,Hao Xia,Xianmin Zhang,Zhizhe Wang,Jun Luo,Hai Li
摘要
The low-vacuum and low-accelerating-voltage modes are the most simple and practical ways to directly analyze poorly conductive samples in conventional scanning electron microscopy (SEM). However, structural feature information may disappear or be obscured in these imaging modes, making it challenging to identify and analyze some local microstructures of poorly conductive samples. To overcome this challenge, an enhanced visualization image acquisition method for samples with poor conductivity is proposed based on the image registration and multi-sensor fusion technology. Experiments demonstrate that the proposed method can effectively obtain enhanced visualization images containing clearer terrain information than the SEM source images, thereby providing new references for measuring and analyzing microstructures.
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