Accurate reconstruction in digital holographic microscopy using antialiasing shift-invariant contourlet transform

Xiaolei Zhang; Xiangchao Zhang; Min Xu; Hao Zhang; Xiangqian Jiang

doi:10.1117/1.OE.57.3.034108

28 March 2018 Accurate reconstruction in digital holographic microscopy using antialiasing shift-invariant contourlet transform

Xiaolei Zhang, Xiangchao Zhang, Min Xu, Hao Zhang, Xiangqian Jiang

Author Affiliations +

Optical Engineering, Vol. 57, Issue 3, 034108 (March 2018). https://doi.org/10.1117/1.OE.57.3.034108

Abstract

The measurement of microstructured components is a challenging task in optical engineering. Digital holographic microscopy has attracted intensive attention due to its remarkable capability of measuring complex surfaces. However, speckles arise in the recorded interferometric holograms, and they will degrade the reconstructed wavefronts. Existing speckle removal methods suffer from the problems of frequency aliasing and phase distortions. A reconstruction method based on the antialiasing shift-invariant contourlet transform (ASCT) is developed. Salient edges and corners have sparse representations in the transform domain of ASCT, and speckles can be recognized and removed effectively. As subsampling in the scale and directional filtering schemes is avoided, the problems of frequency aliasing and phase distortions occurring in the conventional multiscale transforms can be effectively overcome, thereby improving the accuracy of wavefront reconstruction. As a result, the proposed method is promising for the digital holographic measurement of complex structures.

Citation Download Citation

Xiaolei Zhang, Xiangchao Zhang, Min Xu, Hao Zhang, and Xiangqian Jiang "Accurate reconstruction in digital holographic microscopy using antialiasing shift-invariant contourlet transform," Optical Engineering 57(3), 034108 (28 March 2018). https://doi.org/10.1117/1.OE.57.3.034108

Received: 10 January 2018; Accepted: 8 March 2018; Published: 28 March 2018

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KEYWORDS

Digital holography

Holography

Microscopy

Digital filtering

Optical filters

Denoising

Speckle

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