Paper
27 November 2023 Autofocusing of Fresnel zone aperture lensless imaging based on image sharpness metrics
Author Affiliations +
Abstract
Fresnel zone aperture lensless imaging encodes incident light into a hologram-like pattern. However, the uncertain target distance leads to a blurry image with artifacts, which brings challenge to the estimation of object distances. We proposed an autofocusing method for FZA lensless imaging which is a superior solution for distance estimation. The image sharpness metrics are incorporated into the back-propagation process to obtain the focusing distance and reconstruct high-contrast and noise-free images. The Tamura gradient, nuclear norm of gradient and the gradient of the image are combined together to obtain a new evaluation metric. The acquisition accuracy is higher and the time is faster by using this new metric to obtain the focus distance. The proposed method paves the way to the micro sensors.
(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Fangyu Liu, Jiachen Wu, and Liangcai Cao "Autofocusing of Fresnel zone aperture lensless imaging based on image sharpness metrics", Proc. SPIE 12768, Holography, Diffractive Optics, and Applications XIII, 127681F (27 November 2023); https://doi.org/10.1117/12.2688901
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KEYWORDS
Image sharpness

Image restoration

Shadows

Cameras

Image processing

Sensors

Image sensors

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