KEYWORDS: Point spread functions, Particles, Nanoparticles, Phase shift keying, 3D tracking, Objectives, Signal to noise ratio, Optical engineering, Diffusion, Superposition
A well-established method for 3D nanoparticle tracking is the double-helix point spread function (DH-PSF) engineering, which uses additional optical elements to make the PSF exhibit different rotation angles with varying depths of nanoparticles. Splicing the symmetric spiral phases together using the phase splicing method can generate the modulated phase mask of 2π-DH-PSF. The 2π-DH-PSF has a linear rotation rate at each axial position and has a larger rotation angle, showing a more accurate rotation angle and depth translation. Experiments with a phase-only spatial light modulator demonstrate the potential of the 2π-DH-PSF. Finally, we successfully conducted 3D nanoparticle tracking experiments at 8-μm depth with a numerical aperture of 1.4, showing its great potential.
This paper proposes a high-precision characterization method for step height of micro-structured surfaces based on the Kmeans algorithm. First, the original measured surface data obtained by the three-dimensional surface measuring instrument is dimensionally reconstructed. Secondly, use the K-means-based clustering algorithm and data mapping to identify and remove outliers, and the centroid distance of the reconstructed data in the three-dimensional space is mapped to the required step height value. Finally, through the iterative convergence design, the accuracy and robustness of the algorithm characterization results are further improved. Experiment on simulated data shows that this method is robust against outliers. It can effectively and accurately characterize step heights for measurement data of big size. Also, the method can simultaneously ignore outliers during parameterization.
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