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A High-Speed Atomic Force Microscopy with Super Resolution Based on Path Planning Scanning
Ultramicroscopy ( IF 2.2 ) Pub Date : 2020-06-01 , DOI: 10.1016/j.ultramic.2020.112991
Yinan Wu 1 , Yongchun Fang 1 , Chao Wang 1 , Cunhuan Liu 1 , Zhi Fan 1
Affiliation  

An atomic force microscopy generally adopts a raster scanning method to obtain the image of the sample morphology. However, the raster method takes too much time on the base part without focusing enough on the object, thereby restricting the scanning speed of an AFM. To solve this problem, this paper proposes a novel path planning based scanning method to achieve high-speed scanning with super resolution for AFMs. Specifically speaking, a fast scanning process is first carried out to generate a low-resolution image with less time, then a convolutional neural network is designed to construct a super-resolution image based on the fast scanning image. Afterwards, an advanced detection algorithm is proposed to achieve the accurate object detection and localization. Furthermore, an improved ant colony optimization algorithm is proposed to realize the path planning for scanning the objects with high quality, whose imaging result is then matched with the previous super-resolution image to construct the entire sample image, thus achieving fast scanning with super resolution. Experimental and application results demonstrate the good performance of the proposed scanning method.

中文翻译:

基于路径规划扫描的超分辨率高速原子力显微镜

原子力显微镜一般采用光栅扫描的方法来获得样品形貌的图像。然而,光栅方法在基部上花费了太多时间而没有足够地聚焦在物体上,从而限制了 AFM 的扫描速度。为了解决这个问题,本文提出了一种新的基于路径规划的扫描方法,以实现 AFM 的超分辨率高速扫描。具体来说,首先进行快速扫描过程,以较少的时间生成低分辨率图像,然后设计卷积神经网络,基于快速扫描图像构建超分辨率图像。然后,提出了一种先进的检测算法来实现准确的目标检测和定位。此外,提出一种改进的蚁群优化算法,实现对高质量物体扫描的路径规划,将其成像结果与之前的超分辨率图像进行匹配,构建整个样本图像,从而实现超分辨率的快速扫描。实验和应用结果证明了所提出的扫描方法的良好性能。
更新日期:2020-06-01
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