Phase noise reduction in digital holographic microscopy based on adaptive filtering and total directional variation

Digital holographic microscopy (DHM) has been widely used in the biological and medical fields as an important tool for observing microstructures. However, the imaging quality of DHM is impacted by various random noises introduced by the light source and optical components as well as the experimental environment. In order to reduce the effect of random noise, this paper proposes an adaptive filtering and total directional variation (TDV) method based on the change of principal component analysis (PCA) transform domain to reduce the phase noise. The performance of the proposed method is tested by experiments, showing that it can effectively reduce the random noise of the phase image and retain details of the image well.