An optical-digital method of noise suppression in digital holography

Abstract

Digital holography is widely used for the fast and accurate reconstruction of objects and 3D-scenes characteristics: intensity, depth locations, density, temperature, refractive index, etc. There are various types of noise in digital holography, including speckle noise, zero order and twin image, camera shot noise and fixed-pattern noise. Therefore, additional hologram processing is required to obtain a high-quality reconstructed image. This paper proposes an optical-digital method of noise suppression in digital holography. First, a set of uncorrelated holograms is registered. The reconstructed images are treated as a 3D array, to which a 3D filter is then applied. A 3D median filter is used in this study; however, other 3D filters based on weighted average can be utilized also. The proposed method was verified using computer-generated and optically registered digital Fresnel holograms. Even with a small number of images, the method significantly improves the quality: the normalized standard deviation was decreased by up to 3-10 times and speckle contrast was reduced by more than six times. Registration of only ten holograms is sufficient to obtain a quality close to the maximum. The flexibility of the proposed method allows for varying the ratio of the reconstruction quality to the processing time.

Enhancing digital holography through an AI-powered approach for speckle noise reduction and coherence length preservation

“…This random phase is typically modeled as a stochastic process, with its statistical properties closely linked to the characteristics of the illumination source. Notably, fluctuations in speckle noise are generally more pronounced when utilizing a highly coherent light source, compared to what is observed with partially coherent sources [22,23].…”

HoloForkNet: Digital Hologram Reconstruction via Multibranch Neural Network

“…The main problems of digital holography include the presence of zero-order twin images [22][23][24] and optical noises [1,[25][26][27] in reconstructed images. These factors can lead to a decrease in the quality of reconstruction and, therefore, the accuracy of the obtained object images.…”