Singular value decomposition approach to coherent averaging in digital holography

Abstract

We present a new approach to coherent averaging in digital holography using singular value decomposition (SVD). Digital holography enables the extraction of phase information from intensity measurements. For this reason, SVD can be used to statistically determine the orthogonal vectors that align the complex-valued measurements from multiple frames and group common modes accounting for constant phase shift terms. The SVD approach enables the separation of multiple signals, which can be applied to remove undesired artifacts such as scatter in retrieved images. The advantages of the SVD approach are demonstrated here in experiments through fog-degraded holograms with spatially incoherent and coherent scatter. (C) 2020 Optical Society of America