Solving equations after dense scan to improve the resolutions of microscopes

TL;DR

This paper introduces a novel microscopy imaging method that enhances resolution by solving equations derived from targeted dense scans, reducing scanning effort while maintaining high-resolution image recovery.

Contribution

The study proposes a new approach that requires only region-specific scans and solves an equation system to improve resolution, offering efficiency over existing methods.

Findings

Effective in simulated data experiments

More efficient than existing methods at high resolutions

Achieves super-resolution without extensive peripheral scanning

Abstract

Super-resolution techniques overcome the diffraction-limit and get very high resolutions. A category of these techniques, e.g., STED achieves this by creating an illumination spot smaller than the Airy Disk. As a result, points are distinguishable even if they are as small as the spot. In order to further observe structures smaller than the spot itself, a technique called DDS scans the sample more densely, and recovers the expected image by deconvolution. In that technique, the deconvolution is achieved by filtering which requires some peripheral areas to be scanned together with the region of interest. In this study, an approach is proposed which has the same preprocessing stage as DDS. But it requires to scan only the region of interest. After that, an equation system is got from the scanned data. Finally, the expected image is recovered by solving the equation system. Experiments are performed on simulated data, and the results demonstrate the effectiveness of the proposed approach. The experiments also suggest that the proposed approach is more efficient than the existing one especially when the expected resolution is high.