NDLI: Deep Learning for Lensless Compressive Imaging

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Deep Learning for Lensless Compressive Imaging

Content Provider	Semantic Scholar
Author	Yuan, Xin Pu, Yunchen
Copyright Year	2018
Abstract	The lensless compressive camera [1], enjoys low-cost, low-power properties and has demonstrated excellent results using advanced reconstruction algorithms [2]. Furthermore, the same architecture can be used for imaging of visible spectrum, and other spectra such as infrared and millimeter waves. The architecture can also be used to capture hyperspectral images [3] and polarized images [4] by integrating related hardware. However, two disadvantages exist in the current lensless compressive camera, and both are related to speed. Firstly, the capture speed is slow, which limits the applications of the lensless compressive camera. The second one is that the reconstruction algorithm is slow such that user needs to wait, e.g. several minutes, to obtain the reconstructed image.
Starting Page	506
Ending Page	507
Page Count	2
File Format	PDF HTM / HTML
DOI	10.1017/s1431927618003021
Volume Number	24
Alternate Webpage(s)	http://minisites.cambridgecore.org/MAM2018/7337/0506.pdf
Alternate Webpage(s)	https://www.cambridge.org/core/services/aop-cambridge-core/content/view/B5522694F49BB200F699AC9369223E82/S1431927618003021a.pdf/deep_learning_for_lensless_compressive_imaging.pdf
Alternate Webpage(s)	https://doi.org/10.1017/s1431927618003021
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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