Generalized computational framework for phase image reconstruction in structured illumination digital holographic microscopy

Abstract

Correct demodulation and phase compensation are integral in digital holographic microscopy (DHM) with structured illumination (SI), i.e., SI-DHM, to reconstruct super-resolved phase images from raw SI-DHM holograms. The overall performance of the SI-DHM system depends heavily on the computational reconstruction framework utilized. This work presents a generalized reconstruction framework for SI-DHM that automatically demodulates the two laterally shifted object spectrums without prior knowledge of the phase shifts between the recorded holograms and automatically compensates for the linear phase term of each shifted object spectrum. The proposed framework reconstructs super-resolved phase images along one lateral direction with minimum inputs from the user, only requiring the two recorded phase-shifted holograms, the pixel size, and the source's wavelength. The framework's performance has been validated using simulated and experimental holograms recorded using an SI-DHM system for two different lateral modulation frequencies of the structured pattern, demonstrating its versatility and effectiveness in reconstructing super-resolved phase images.