Passive time-multiplexing super-resolved technique for axially moving targets

Abstract

In this paper we present a super-resolving approach for detecting an axially moving target that is based upon a time-multiplexing concept and that overcomes the diffraction limit set by the optics of an imaging camera by a priori knowledge of the high-resolution background in front of which the target is moving. As the movement trajectory is axial, the approach can be applied to targets that are approaching or moving away from the camera. By recording a set of low-resolution images at different target axial positions, the super-resolving algorithm weights each image by demultiplexing them using the high-resolution background image and provides a super-resolved image of the target. Theoretical analyses as well as simulations and preliminary experimental validation are presented to validate the proposed approach.

Optical-tweezing-based linear-optics nanoscopy

“…Importantly, unlike in the mentioned algorithms [35], [36], where a random pattern was overlayed with the sample to increase the resolution, we scan the sample by just one (or several) individual particles. Therefore, the correlation D is not a perfect δ-function and should be calculated according to the particle size and a model of reflectance from the nanoparticles.…”