| 摘要(英) |
This study aims to explore the design of an optical system based on holography theory, utilizing a coaxial configuration to simplify equipment requirements and achieve miniaturization. Traditional holography requires extensive and complex optical equipment. In contrast, our designed system only needs a near-coaxial light source and sensor to capture an image area of nearly 30mm² in a single shot, equivalent to eight times the area under a 20x objective lens of a conventional microscope. In terms of image reconstruction, we innovatively proposed an algorithm that filters critical information through image masking based on the traditional holography reconstruction method (ASP), successfully solving the concentric circle issue in coaxial holography image reconstruction. Additionally, this study integrates the latest artificial intelligence technology by employing deep learning models to replace the mathematical theory of holography for image reconstruction. Through tests with different samples, the feasibility and effectiveness of this model have been demonstrated. We also combined noise reduction and resolution enhancement models, further improving the quality of reconstructed images. The comprehensive application of these technologies allows us to significantly enhance the clarity and accuracy of the images.
The results of this study demonstrate the great potential of combining lensless holographic microscopy systems with artificial intelligence technology, especially its application value in simplifying optical equipment, improving image quality, and achieving system miniaturization. In the future, we look forward to further optimizing the system and adding more advanced functions and applications to make it play a more significant role in various fields. Keywords: holography, deep learning, image reconstruction, image quality enhancement, miniaturized system. |
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