Fourier Analysis of Interference Scanning Optical Probe Microscopy

IF 4.8 2区 计算机科学 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Emmanuel Soubies;Wolfgang Bacsa
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引用次数: 0

Abstract

As opposed to popular far-field and near-field optical microscopy techniques, Interference Scanning Optical probe Microscopy (ISOM) operates in the intermediate-field region, where the probing distance is typically of the order of the wavelength of incident light. Specifically, ISOM enables the imaging of nanostructures through numerical inverse scattering of standing waves generated by the interference between the incident (or reflected) and scattered waves. In this work, we shed new light on this microscopy modality through an in-depth Fourier analysis. Our analysis reveals insights on the required acquisition sampling step as well as on the resolution limit of the system. Moreover, we propose two novel methods to address the associated inverse scattering problem, leveraging the intrinsic structure of the image formation model to reduce computational complexity and sensitivity to errors in model parameters. Finally, we illustrate our theoretical findings with numerical experiments.
干涉扫描光学探针显微镜的傅里叶分析
与流行的远场和近场光学显微镜技术相反,干涉扫描光学探针显微镜(ISOM)在中间场区域工作,其中探测距离通常是入射光波长的数量级。具体来说,ISOM通过入射波(或反射波)和散射波之间的干涉产生的驻波的数值逆散射来实现纳米结构的成像。在这项工作中,我们通过深入的傅立叶分析揭示了这种显微镜形态的新亮点。我们的分析揭示了所需的采集采样步骤以及系统的分辨率限制的见解。此外,我们提出了两种新的方法来解决相关的逆散射问题,利用图像形成模型的内在结构来降低计算复杂度和对模型参数误差的敏感性。最后,我们用数值实验来说明我们的理论发现。
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来源期刊
IEEE Transactions on Computational Imaging
IEEE Transactions on Computational Imaging Mathematics-Computational Mathematics
CiteScore
8.20
自引率
7.40%
发文量
59
期刊介绍: The IEEE Transactions on Computational Imaging will publish articles where computation plays an integral role in the image formation process. Papers will cover all areas of computational imaging ranging from fundamental theoretical methods to the latest innovative computational imaging system designs. Topics of interest will include advanced algorithms and mathematical techniques, model-based data inversion, methods for image and signal recovery from sparse and incomplete data, techniques for non-traditional sensing of image data, methods for dynamic information acquisition and extraction from imaging sensors, software and hardware for efficient computation in imaging systems, and highly novel imaging system design.
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