典型文献
Spectral imaging with deep learning
文献摘要：
The goal of spectral imaging is to capture the spectral signature of a target.Traditional scanning method for spectral imaging suffers from large system volume and low image acquisition speed for large scenes.In contrast,computational spectral imaging methods have resorted to computation power for reduced system volume,but still endure long computation time for iterative spectral reconstructions.Recently,deep learning techniques are introduced into computational spectral imaging,witnessing fast reconstruction speed,great reconstruction quality,and the potential to drastically reduce the system volume.In this article,we review state-of-the-art deep-learning-empowered computational spectral imaging methods.They are further divided into amplitude-coded,phase-coded,and wavelength-coded methods,based on different light properties used for encoding.To boost future researches,we've also organized publicly available spectral datasets.
文献关键词：
中图分类号：
作者姓名：
Longqian Huang;Ruichen Luo;Xu Liu;Xiang Hao
作者机构：
State Key Laboratory of Modern Optical Instrumentation,College of Optical Science and Technology,Zhejiang University,Hangzhou 310027,China;College of Computer Science and Technology,Zhejiang University,Hangzhou 310027,China;Jiaxing Key Laboratory of Photonic Sensing&Intelligent Imaging,Jiaxing 314000,China;Intelligent Optics&Photonics Research Center,Jiaxing Research Institute Zhejiang University,Jiaxing 314000,China
文献出处：
引用格式：
[1]Longqian Huang;Ruichen Luo;Xu Liu;Xiang Hao-.Spectral imaging with deep learning)[J].光：科学与应用（英文版）,2022(06):1040-1058
A类：
resorted
B类：
Spectral,imaging,deep,learning,goal,spectral,capture,signature,target,Traditional,scanning,suffers,from,large,system,volume,low,image,acquisition,speed,scenes,In,contrast,computational,methods,have,reduced,but,still,endure,long,iterative,reconstructions,Recently,techniques,are,introduced,into,witnessing,fast,great,quality,potential,drastically,this,article,review,state,empowered,They,further,divided,amplitude,coded,phase,wavelength,different,light,properties,used,encoding,To,boost,future,researches,also,organized,publicly,available,datasets
AB值：
0.57032
相似文献
机标中图分类号，由域田数据科技根据网络公开资料自动分析生成，仅供学习研究参考。
