Super-resolution macroscopic imaging via unknown speckle illumination using sparse aperture transmitter

Abstract

Optical sparse aperture imaging technology has promising applications in the next generation of high-resolution imaging systems, but the phasing errors correction of sparse aperture is an urgent problem to be addressed. In this paper, we propose a blind structured-illumination super-resolution imaging system using a sparse aperture as the transmitter to overcome phasing errors and obtain higher resolution. In our scheme, an unknown pattern is projected onto the object by a sparse aperture system. By translating the unknown pattern, a sequence of modulated raw images is obtained. Based on these low-resolution raw images, the super-resolution object and the unknown illumination pattern are jointly estimated by the Adam algorithm. Here we show, both in the simulation and experiment, the resolution of reconstructions using sparse aperture as transmitter are similar to those using monolithic lens. Furthermore, we validate that the proposed method can protect the reconstruction effect from piston error and widen the tolerance range of tip/tilt error (peak-valley values) up to 0.5λ. At the same time, our proposed system can also alleviate to some extent the problem of mid-frequency modulation transfer function (MTF) attenuation that exists in sparse aperture imaging. Our approach not only simplifies the process of constructing synthetic aperture system, but also provides a novel application for synthetic aperture systems.