Noise reduction method using a variance map of the phase differences in digital holographic microscopy

The phase reconstruction process in digital holographic microscopy involves a trade‐off between the phase error and the high‐spatial‐frequency components. In this reconstruction process, if the narrow region of the sideband is windowed in the Fourier domain, the phase error from the DC component will be reduced, but the high‐spatial‐frequency components will be lost. However, if the wide region is windowed, the 3D profile will include the high‐spatial‐frequency components, but the phase error will increase. To solve this trade‐off, we propose the high‐variance pixel averaging method, which uses the variance map of the reconstructed depth profiles of the windowed sidebands of different sizes in the Fourier domain to classify the phase error and the high‐spatial‐frequency components. Our proposed method calculates the average of the high‐variance pixels because they include the noise from the DC component. In addition, for the nonaveraged pixels, the reconstructed phase data created by the spatial frequency components of the widest window are used to include the high‐spatial‐frequency components. We explain the mathematical algorithm of our proposed method and compare it with conventional methods to verify its advantages.