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Single-shot lensless imaging with fresnel zone aperture and incoherent illumination

Authors :
Jiachen Wu
Wenhui Zhang
Liangcai Cao
Hua Zhang
George Barbastathis
Guofan Jin
Source :
Light: Science & Applications, Vol 9, Iss 1, Pp 1-11 (2020), Light, Science & Applications
Publication Year :
2020
Publisher :
Nature Publishing Group, 2020.

Abstract

Lensless imaging eliminates the need for geometric isomorphism between a scene and an image while allowing the construction of compact, lightweight imaging systems. However, a challenging inverse problem remains due to the low reconstructed signal-to-noise ratio. Current implementations require multiple masks or multiple shots to denoise the reconstruction. We propose single-shot lensless imaging with a Fresnel zone aperture and incoherent illumination. By using the Fresnel zone aperture to encode the incoherent rays in wavefront-like form, the captured pattern has the same form as the inline hologram. Since conventional backpropagation reconstruction is troubled by the twin-image problem, we show that the compressive sensing algorithm is effective in removing this twin-image artifact due to the sparsity in natural scenes. The reconstruction with a significantly improved signal-to-noise ratio from a single-shot image promotes a camera architecture that is flat and reliable in its structure and free of the need for strict calibration.<br />Lensless imaging: reduced noise Two simple innovations have been found to significantly improve the quality of lensless imaging. Jiachen Wu and coworkers from Tsinghua University in China and MIT in the US report that introducing a Fresnel optical element and applying a compressive sensing algorithm can significantly reduce the level of noise in reconstructed images. Their simple lensless system consists of a Fresnel Zone Aperture (FZA) placed 3 mm in front of a CMOS image sensor. The FZA is a mask of patterned chrome that consists of a series of concentric rings that alternatingly transmit and block light. Images on an LCD screen placed ~30 cm from the mask are used as a test object. The signal recorded by the CMOS sensor is then reconstructed by a compressive sensing algorithm with total variation denoising to generate an improved image of the object.

Details

Language :
English
ISSN :
20477538
Volume :
9
Issue :
1
Database :
OpenAIRE
Journal :
Light: Science & Applications
Accession number :
edsair.doi.dedup.....9061466f42f3d253111b92642712af56