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Volume 25
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10.3390/s25103221
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

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

by
Chen Yu
1,2,
Ying Liu
1,*,
Linhan Li
1,2,
Guangpeng Zhou
1,2,
Boshi Dang
1,
Jie Du
1,
Junlin Ma
1 and
Site Zhang
1
1
Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
*
Author to whom correspondence should be addressed.
Sensors 2025, 25(10), 3221; https://doi.org/10.3390/s25103221
Submission received: 21 April 2025 / Revised: 12 May 2025 / Accepted: 20 May 2025 / Published: 20 May 2025
(This article belongs to the Section Optical Sensors)
Versions Notes

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.
Keywords: elimination of diffraction spots; microscopy; fast autofocus; computer vision elimination of diffraction spots; microscopy; fast autofocus; computer vision

Share and Cite

MDPI and ACS Style

Yu, C.; Liu, Y.; Li, L.; Zhou, G.; Dang, B.; Du, J.; Ma, J.; Zhang, S. Super-Resolution Image Optimisation Based on Gradient Iterative Fast Diffraction-Free Spot Algorithm. Sensors 2025, 25, 3221. https://doi.org/10.3390/s25103221

AMA Style

Yu C, Liu Y, Li L, Zhou G, Dang B, Du J, Ma J, Zhang S. Super-Resolution Image Optimisation Based on Gradient Iterative Fast Diffraction-Free Spot Algorithm. Sensors. 2025; 25(10):3221. https://doi.org/10.3390/s25103221

Chicago/Turabian Style

Yu, Chen, Ying Liu, Linhan Li, Guangpeng Zhou, Boshi Dang, Jie Du, Junlin Ma, and Site Zhang. 2025. "Super-Resolution Image Optimisation Based on Gradient Iterative Fast Diffraction-Free Spot Algorithm" Sensors 25, no. 10: 3221. https://doi.org/10.3390/s25103221

APA Style

Yu, C., Liu, Y., Li, L., Zhou, G., Dang, B., Du, J., Ma, J., & Zhang, S. (2025). Super-Resolution Image Optimisation Based on Gradient Iterative Fast Diffraction-Free Spot Algorithm. Sensors, 25(10), 3221. https://doi.org/10.3390/s25103221

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