Single-shot microscopic autofocus focusing on image detail features

Zhijie Hua; Xu Zhang; Dawei Tu; Jiale Chen; Mengting Qian

doi:10.1117/12.3021718

15 February 2024 Single-shot microscopic autofocus focusing on image detail features

Zhijie Hua, Xu Zhang, Dawei Tu, Jiale Chen, Mengting Qian

Proceedings Volume 13069, International Conference on Optical and Photonic Engineering (icOPEN 2023); 130690C (2024) https://doi.org/10.1117/12.3021718
Event: International Conference on Optical and Photonic Engineering (icOPEN 2023), 2023, Singapore, Singapore

Abstract

Autofocus plays an important role in microscopic imaging. As an extension of image-based methods, learning-based methods make real-time autofocus possible. The recently proposed learning-based autofocus methods achieved promising results in estimating defocus distance. However, the focusing accuracy depends partly on the feature extraction ability of the network model, and what features are specifically extracted by the network contributed to its success remains a mystery. In this paper, a single-shot microscopic autofocus method was proposed, which predicts the defocus distance from a single natural image, to improve the model's ability to extract image detail features. Furthermore, we validate that the neural network model mainly predicts the defocus distance by focusing on the sharpness of texture and edge features, and visualize the weight of the predicting results. A realistic dataset of sufficient size was made to train all models. The experiment shows the proposed network model has better focusing accuracy compared with other models, with a mean focusing error of 0.44μm, and pays more attention to the texture and edge features.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zhijie Hua, Xu Zhang, Dawei Tu, Jiale Chen, and Mengting Qian "Single-shot microscopic autofocus focusing on image detail features", Proc. SPIE 13069, International Conference on Optical and Photonic Engineering (icOPEN 2023), 130690C (15 February 2024); https://doi.org/10.1117/12.3021718

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KEYWORDS

Feature extraction

Image sharpness

Education and training

Point spread functions

Image processing

Data modeling

Neural networks

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