Averaging fractional Fourier domains for background noise removal applied to digital lensless holographic microscopy

Abstract

A background noise removal method based on averaging fractional Fourier domains is presented. The method is applied to Digital Lensless Holographic Microscopy (DLHM) intensity reconstructions, where the background is perturbed by the weak yet detrimental presence of information of the twin image. A set of fractional Fourier domains of a DLHM intensity reconstruction is computed and thereafter averaged leading to a sensible reduction of the background noise and, therefore, an increase in the overall contrast of the resulting image. The maximum reach of the fractional rotations used in the method is determined by measuring the spatial resolution in a regular star test target such that the spatial resolution is kept within the span of interest for a given application. The set of images to be averaged is composed of fractional rotations of the original intensity reconstruction that are smaller than the previously determined maximum reach. The number of fractional rotations that are finally averaged is determined by the sought increase in the contrast of the resulting image. Experimental samples of micrometer-sized objects and an intricate biological specimen have been used to validate the proposal.