Automatic Spatial Filtering by Combining Wavelet-Transform Modal Maxima and Mathematical Morphology in Digital Holographic Microscopy

Abstract

Digital holographic microscopy has significant advantages over traditional 3D measurements. In order to obtain a reconstructed image of superior quality, the zero-order-term spectrum and the −1 term spectrum must be eliminated during the digital reconstruction. At the same time, digital holographic microscopy has changed from the traditional manual selection of the +1 term spectrum to the automatic selection of the +1 term spectrum. In the process of spatial filtering of the +1 term spectrum, the filtering window is crucial, and the shape of the filtering window and the robustness of the filtering window to noise will ultimately affect the reconstruction results. In this paper, we propose an automatic spatial filtering method that combines wavelet transform and mathematical morphology to automatically extract the +1 term spectrum. Compared with conventional methods, the reconstruction results are more accurate and robust to noise, and the experimental results verify the feasibility of the proposed method.