# Super-Resolution Image Optimisation Based on Gradient Iterative Fast Diffraction-Free Spot Algorithm

## TL;DR

This paper introduces a new algorithm that improves laser image quality by removing diffraction effects, achieving super-resolution in microscopy.

## Contribution

A novel gradient iterative algorithm is proposed to rapidly remove diffraction interference and achieve super-resolution.

## Key findings

- The algorithm increases interlayer resolution to a quarter of the original value.
- The method surpasses the microscope's inherent resolution capabilities.
- Improved convergence of the iterative process was achieved with the new calculation model.

## Abstract

Diffraction significantly deteriorates the quality of the laser image, causing severe degradation that undermines the theoretical performance parameters of the autofocus system. In this paper, we conduct a comprehensive analysis of the non-uniform features of the images. To enhance the imaging quality of each individual image, we propose a de-diffraction algorithm based on gradient iteration. This algorithm is capable of rapidly removing the interference spots resulting from diffraction and restoring the distorted laser spots. By doing so, it effectively eliminates the inevitable reduction in the autofocus resolution and focusing accuracy caused by diffraction. Furthermore, the proposed calculation model for the intra-localisation interval significantly improves the convergence of the iterative calculation process. Through experiments, it has been verified that, under the same conditions, the interlayer resolution between the reflective surfaces of the samples processed using this algorithm is increased to a quarter of the original value. This remarkable improvement in resolution, which far exceeds the microscope’s inherent resolution, demonstrates that the algorithm successfully achieves super-resolution for the microscope.