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Fresnel aperture coding lensless imaging based on adaptive weighted TVAL3 regularization algorithm
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DOI：10.1016/j.optcom.2025.132543.png)
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Abstract
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Lensless imaging shifts the burden of imaging from bulky and expensive hardware to computing, which enables new architectures for portable cameras. However, the twin image effect caused by the missing phase information in the light wave is a key factor limiting the quality of lensless imaging. To improve imaging quality, this paper proposes the use of the adaptive weighted augmented Lagrangian function method and alternating direction method to achieve Fresnel aperture encoded lensless imaging reconstruction. The experimental results show that the algorithm used in this paper can improve the quality of reconstructed images and restore more details of the images.
Keywords:
Lensless imaging
Fresnel aperture
Coded mask
Imaging reconstruction
Journal
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2.5
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606
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Cited Papers
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