Hagemeier Sebastian, Pahl Tobias, Breidenbach Johannes, Lehmann Peter
Measurement Technology, Department of Electrical Engineering and Computer Science, University of Kassel, Kassel, Germany.
Microsc Res Tech. 2023 Aug;86(8):1012-1022. doi: 10.1002/jemt.24376. Epub 2023 Jun 26.
The depth discrimination in confocal microscopy is based on the digital analysis of depth response signals obtained by each camera pixel during measurement. Various signal-processing algorithms are used for this purpose. The accuracy of these algorithms is inter alia restricted by the axial symmetry of the signals. However, in practice response signals are rather asymmetrical especially in case of measurement objects with critical surface structures such as edges or steep flanks. We present a novel signal-processing algorithm based on an exponential function with a cubic argument to handle asymmetrical and also symmetrical depth response signals. Results obtained by this algorithm are compared to those of commonly used signal processing algorithms. It turns out that the novel algorithm is more robust, more accurate and exhibits a repeatability of a similar order compared to other algorithms. RESEARCH HIGHLIGHTS: A novel, more robust algorithm with improved accuracy in peak extraction especially for asymmetrical response signals in confocal microscopy is introduced and validated. Improved accuracy is demonstrated for height and layer thickness measurements.
共聚焦显微镜中的深度分辨基于对测量过程中每个相机像素获得的深度响应信号进行数字分析。为此使用了各种信号处理算法。这些算法的准确性尤其受到信号轴对称性的限制。然而，在实际中，响应信号相当不对称，特别是在具有诸如边缘或陡峭侧面等临界表面结构的测量对象的情况下。我们提出了一种基于具有三次方自变量的指数函数的新型信号处理算法，以处理不对称和对称的深度响应信号。将该算法获得的结果与常用信号处理算法的结果进行比较。结果表明，与其他算法相比，新算法更稳健、更准确，并且具有相似的重复性。研究亮点：引入并验证了一种新型、更稳健的算法，该算法在峰值提取方面具有更高的准确性，特别是对于共聚焦显微镜中的不对称响应信号。在高度和层厚测量中证明了准确性的提高。
