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

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 quali...

Full description

Saved in:
Bibliographic Details
Main Authors: Chen Yu, Ying Liu, Linhan Li, Guangpeng Zhou, Boshi Dang, Jie Du, Junlin Ma, Site Zhang
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Sensors
Subjects:
Online Access:https://www.mdpi.com/1424-8220/25/10/3221
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849719437737852928
author Chen Yu
Ying Liu
Linhan Li
Guangpeng Zhou
Boshi Dang
Jie Du
Junlin Ma
Site Zhang
author_facet Chen Yu
Ying Liu
Linhan Li
Guangpeng Zhou
Boshi Dang
Jie Du
Junlin Ma
Site Zhang
author_sort Chen Yu
collection DOAJ
description 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.
format Article
id doaj-art-85eda221e9c541e7bdc855ae2c2c6f84
institution DOAJ
issn 1424-8220
language English
publishDate 2025-05-01
publisher MDPI AG
record_format Article
series Sensors
spelling doaj-art-85eda221e9c541e7bdc855ae2c2c6f842025-08-20T03:12:09ZengMDPI AGSensors1424-82202025-05-012510322110.3390/s25103221Super-Resolution Image Optimisation Based on Gradient Iterative Fast Diffraction-Free Spot AlgorithmChen Yu0Ying Liu1Linhan Li2Guangpeng Zhou3Boshi Dang4Jie Du5Junlin Ma6Site Zhang7Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, ChinaChangchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, ChinaDiffraction 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.https://www.mdpi.com/1424-8220/25/10/3221elimination of diffraction spotsmicroscopyfast autofocuscomputer vision
spellingShingle Chen Yu
Ying Liu
Linhan Li
Guangpeng Zhou
Boshi Dang
Jie Du
Junlin Ma
Site Zhang
Super-Resolution Image Optimisation Based on Gradient Iterative Fast Diffraction-Free Spot Algorithm
Sensors
elimination of diffraction spots
microscopy
fast autofocus
computer vision
title Super-Resolution Image Optimisation Based on Gradient Iterative Fast Diffraction-Free Spot Algorithm
title_full Super-Resolution Image Optimisation Based on Gradient Iterative Fast Diffraction-Free Spot Algorithm
title_fullStr Super-Resolution Image Optimisation Based on Gradient Iterative Fast Diffraction-Free Spot Algorithm
title_full_unstemmed Super-Resolution Image Optimisation Based on Gradient Iterative Fast Diffraction-Free Spot Algorithm
title_short Super-Resolution Image Optimisation Based on Gradient Iterative Fast Diffraction-Free Spot Algorithm
title_sort super resolution image optimisation based on gradient iterative fast diffraction free spot algorithm
topic elimination of diffraction spots
microscopy
fast autofocus
computer vision
url https://www.mdpi.com/1424-8220/25/10/3221
work_keys_str_mv AT chenyu superresolutionimageoptimisationbasedongradientiterativefastdiffractionfreespotalgorithm
AT yingliu superresolutionimageoptimisationbasedongradientiterativefastdiffractionfreespotalgorithm
AT linhanli superresolutionimageoptimisationbasedongradientiterativefastdiffractionfreespotalgorithm
AT guangpengzhou superresolutionimageoptimisationbasedongradientiterativefastdiffractionfreespotalgorithm
AT boshidang superresolutionimageoptimisationbasedongradientiterativefastdiffractionfreespotalgorithm
AT jiedu superresolutionimageoptimisationbasedongradientiterativefastdiffractionfreespotalgorithm
AT junlinma superresolutionimageoptimisationbasedongradientiterativefastdiffractionfreespotalgorithm
AT sitezhang superresolutionimageoptimisationbasedongradientiterativefastdiffractionfreespotalgorithm