Extracting focus variation data from coherence scanning interferometric measurements

Liu, Jiayu; Hooshmand, Helia; Piano, Samanta; Leach, Richard; Coupland, Jeremy; Ren, Mingjun; Zhu, Limin; Su, Rong

Abstract

Coherence scanning interferometry (CSI), based on the principle of interference, can achieve sub-nanometer precision for height measurements. On the other hand, focus variation microscopy (FVM), combining the small depth of field of the objective, is a widely used surface topography measurement method suited to surface topography that is mostly optically rough. In this paper, we propose a method to simultaneously obtain the interferometric fringe data and focus variation FVM image stack, from a single vertical scanning process, using a CSI instrument without any hardware modifications. Using a 3D Fourier transform, the FVM signal, looks takes the form of a “bowtie” and the CSI signal resembles two “umbrellas” that are separated in 3D K-space. The signal is recovered using a 3D inverse Fourier transform and the surface topography can be determined by fusing the CSI and FVM signals. Since both signals come from the same instrument and scanning process, there is no need for coordinate registration and data interpolation during the data fusion process. Our method combines the features of CSI and FVM measurement, thereby improving the robustness and data coverage of the measurement. An all-in-focus surface topography map can also be generated using this method. This focusing feature has the potential to significantly improve the defect detection and quality control ability of CSI instruments.

Citation

Liu, J., Hooshmand, H., Piano, S., Leach, R., Coupland, J., Ren, M., Zhu, L., & Su, R. (2024). Extracting focus variation data from coherence scanning interferometric measurements. Precision Engineering, 88, 699-706. https://doi.org/10.1016/j.precisioneng.2024.04.016

• Journal Article Type: Article
• Acceptance Date: Apr 17, 2024
• Online Publication Date: Apr 18, 2024
• Publication Date: Apr 18, 2024
• Deposit Date: Apr 25, 2024
• Journal: Precision Engineering
• Print ISSN: 0141-6359
• Electronic ISSN: 0141-6359
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 88
• Pages: 699-706
• DOI: https://doi.org/10.1016/j.precisioneng.2024.04.016
• Keywords: General Engineering
• Public URL: https://nottingham-repository.worktribe.com/output/33839408
• Publisher URL: https://www.sciencedirect.com/science/article/abs/pii/S0141635924000801?via%3Dihub