This work is related to an Independent study of a senior ECEE student at the University of Memphis, Kamesh Balachandran, finished in May 2023. Results of this study were presented as a Poster in the 2023 Optica Imaging and Applied Optics Congress held in Boston (August 14-17).
A Digital Holographic Microscope (DHM) is an advanced optical interferometer that utilizes a microscopic imaging system to capture interference patterns, allowing for the reconstruction of amplitude and phase images of unstained samples. In-line DHM systems are characterized by completely aligned interfering beams, typically achieved by setting the interference angle to zero. Traditionally, reconstruction algorithms for in-line DHM systems rely on phase-shifting methods, which involve recording multiple interference patterns with laterally shifted fringes. These conventional methods require accurate knowledge of the phase shifts between the recorded holograms, which can be challenging to obtain experimentally and may lead to distorted and unreliable phase maps when inaccurate values are used. As an alternative, blind phase-shifting algorithms, which do not require prior knowledge of the phase shifts, have been proposed. In this undergraduate research project, we aim to explore the performance of an alternative approach based on Principal Component Analysis (PCA) for phase reconstruction in an in-line DHM system. In 2011, Vargas et al. proposed an approach based on PCA for reconstructing both amplitude and phase distributions in DHM [1]. In this undergraduate research project, we aim to investigate the performance of the PCA-based method for phase reconstruction in an in-line DHM system. Specifically, we will evaluate the accuracy and robustness of PCA-based phase reconstruction algorithms based on the number of phase-shifted images and the value of the phase step. The PCA algorithm will be tested under both noiseless and noisy conditions to assess its reliability in practical imaging scenarios. This research project seeks to contribute to the understanding of the potential of PCA as a viable method for phase reconstruction in DHM and its applicability in real-world imaging applications.