Enhanced resolution in lensless in-line holographic microscope by data interpolation and iterative reconstruction

Abstract

In a compact lensless in-line holographic microscope, the imaging resolution is generally limited by the sensor pixel size because of the short sample-to-sensor distance. To overcome this problem, we propose to use data interpolation based on iteration with only two intensity measurements to enhance the resolution in holographic reconstruction. We did numerical simulations using the U.S. air force target as the sample and showed that data interpolation in the acquired in-line hologram can be used to enhance the reconstruction resolution. The imaging resolution and contrast can be further improved by combining data interpolation with iterative holographic reconstruction using only two hologram measurements acquired by slightly changing the sample-to-sensor distance while recording the in-line holograms. The two in-line hologram intensity measurements were used as a priori constraint in the iteration process according to the Gerchberg–Saxton algorithm for phase retrieval. The iterative reconstruction results showed that the iteration between the sample plane and the sensor planes can refine the interpolated data and thus further improve the resolution as well as the imaging contrast. Besides numerical simulation, we also experimentally demonstrated the enhancement of imaging resolution and contrast by imaging the U.S. air force target and a microscope slide of filamentous algae.