Computational Spectral Imaging Based on Compressive Sensing

被引：8

作者：

Wang, Chao ^{[1
,2
,3
]}

Liu, Xue-Feng ^{[3
]}

Yu, Wen-Kai ^{[1
]}

Yao, Xu-Ri ^{[3
]}

Zheng, Fu ^{[3
]}

Dong, Qian ^{[3
]}

Lan, Ruo-Ming ^{[4
]}

Sun, Zhi-Bin ^{[3
]}

Zhai, Guang-Jie ^{[3
]}

Zhao, Qing ^{[1
]}

机构：

[1] Beijing Inst Technol, Sch Phys, Ctr Quantum Technol Res, Beijing 100081, Peoples R China

[2] China Acad Engn Phys, Mianyang 621900, Peoples R China

[3] Chinese Acad Sci, Key Lab Elect & Informat Technol Space Syst, Natl Space Sci Ctr, Beijing 100190, Peoples R China

[4] Shandong Normal Univ, Sch Phys & Elect, Jinan 250014, Shandong, Peoples R China

来源：

CHINESE PHYSICS LETTERS | 2017年 / 34卷 / 10期

基金：

中国国家自然科学基金;

关键词：

PROJECTIONS;

D O I：

10.1088/0256-307X/34/10/104203

中图分类号：

O4 [物理学];

学科分类号：

0702 ;

摘要：

Spectral imaging is an important tool for a wide variety of applications. We present a technique for spectral imaging using computational imaging pattern based on compressive sensing (CS). The spectral and spatial information is simultaneously obtained using a fiber spectrometer and the spatial light modulation without mechanical scanning. The method allows high-speed, stable, and sub sampling acquisition of spectral data from specimens. The relationship between sampling rate and image quality is discussed and two CS algorithms are compared.

引用

页数：5

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