Quantum-inspired computational imaging

被引:162
作者
Altmann, Yoann [1 ]
McLaughlin, Stephen [1 ]
Padgett, Miles J. [2 ]
Goyal, Vivek K. [3 ]
Hero, Alfred O. [4 ]
Faccio, Daniele [2 ]
机构
[1] Heriot Watt Univ, Sch Engn & Phys Sci, Edinburgh, Midlothian, Scotland
[2] Univ Glasgow, Sch Phys & Astron, Glasgow, Lanark, Scotland
[3] Boston Univ, Dept Elect & Comp Engn, Boston, MA 02215 USA
[4] Univ Michigan, Dept Elect Engn & Comp Sci, Ann Arbor, MI 48109 USA
基金
美国国家科学基金会; 英国工程与自然科学研究理事会;
关键词
MULTISPECTRAL LIDAR; KILOMETER-RANGE; PHOTON; CLASSIFICATION; PHOTOGRAPHY; DESIGN; IMAGES;
D O I
10.1126/science.aat2298
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Computational imaging combines measurement and computational methods with the aim of forming images even when the measurement conditions are weak, few in number, or highly indirect. The recent surge in quantum-inspired imaging sensors, together with a new wave of algorithms allowing on-chip, scalable and robust data processing, has induced an increase of activity with notable results in the domain of low-light flux imaging and sensing. We provide an overview of the major challenges encountered in low-illumination (e.g., ultrafast) imaging and how these problems have recently been addressed for imaging applications in extreme conditions. These methods provide examples of the future imaging solutions to be developed, for which the best results are expected to arise from an efficient codesign of the sensors and data analysis tools.
引用
收藏
页码:660 / +
页数:8
相关论文
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