Trends in Snapshot Spectral Imaging: Systems, Processing, and Quality

被引:0
|
作者
Thomas, Jean-Baptiste [1 ,2 ]
Lapray, Pierre-Jean [3 ]
Le Moan, Steven [2 ]
机构
[1] Univ Bourgogne Europe, Dept Informat Elect Mecan IEM, Imagerie & Vis Artificielle ImVIA Lab, F-21000 Dijon, France
[2] NTNU Norwegian Univ Sci & Technol, Dept Comp Sci, N-2815 Gjovik, Norway
[3] Univ Haute Alsace, Inst Res Comp Sci Math Automat & Signal, IRIMAS UR 7499, F-68100 Mulhouse, Alsace, France
关键词
spectral imaging; snapshot spectral imaging; image reconstruction; image quality; DYNAMIC-RANGE; FILTER; COLOR; DEMOSAICKING; RESOLUTION; IMAGES; REPRESENTATION; ACQUISITION; SURFACE; DESIGN;
D O I
10.3390/s25030675
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Recent advances in spectral imaging have enabled snapshot acquisition, as a means to mitigate the impracticalities of spectral imaging, e.g., expert operators and cumbersome hardware. Snapshot spectral imaging, e.g., in technologies like spectral filter arrays, has also enabled higher temporal resolution at the expense of the spatio-spectral resolution, allowing for the observation of temporal events. Designing, realising, and deploying such technologies is yet challenging, particularly due to the lack of clear, user-meaningful quality criteria across diverse applications, sensor types, and workflows. Key research gaps include optimising raw image processing from snapshot spectral imagers and assessing spectral image and video quality in ways valuable to end-users, manufacturers, and developers. This paper identifies several challenges and current opportunities. It proposes considering them jointly and suggests creating a new unified snapshot spectral imaging paradigm that would combine new systems and standards, new algorithms, new cost functions, and quality indices.
引用
收藏
页数:22
相关论文
共 50 条
  • [41] Snapshot Spectral and Polarimetric Imaging; Target Identification with Multispectral Video
    Bartlett, Brent D.
    Rodriguez, Mikel D.
    ALGORITHMS AND TECHNOLOGIES FOR MULTISPECTRAL, HYPERSPECTRAL, AND ULTRASPECTRAL IMAGERY XIX, 2013, 8743
  • [42] Data-driven Prior for Pharmaceutical Snapshot Spectral Imaging
    Su, Xuesan
    Mao, Jianxu
    Wang, Yaonan
    Chen, Yurong
    Zhang, Hui
    2022 IEEE 25TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND ENGINEERING, CSE, 2022, : 38 - 44
  • [43] Snapshot compressive spectral depth imaging from coded aberrations
    Marquez, Miguel
    Meza, Pablo
    Rojas, Fernando
    Arguello, Henry
    Vera, Esteban
    OPTICS EXPRESS, 2021, 29 (06) : 8142 - 8159
  • [44] Single disperser design for coded aperture snapshot spectral imaging
    Wagadarikar, Ashwin
    John, Renu
    Willett, Rebecca
    Brady, David
    APPLIED OPTICS, 2008, 47 (10) : B44 - B51
  • [45] Snapshot Spectral Imaging using Optimized Diffractive Optical Elements
    De Biasio, Martin
    Arnold, Thomas
    Tortschanoff, Andreas
    Hermerschmidt, Andreas
    Leitner, Raimund
    NEXT-GENERATION SPECTROSCOPIC TECHNOLOGIES V, 2012, 8374
  • [46] High-throughput snapshot spectral imaging in two dimensions
    Harvey, AR
    Fletcher-Holmes, DW
    SPECTRAL IMAGING: INSTRUMENTATION, APPLICATIONS, AND ANALYSIS II, 2003, 4959 : 46 - 54
  • [47] High light efficiency snapshot spectral imaging via spatial multiplexing and spectral mixing
    Zhang, Maoqing
    Wang, Lizhi
    Zhang, Lei
    Huang, Hua
    OPTICS EXPRESS, 2020, 28 (14) : 19837 - 19850
  • [48] Deep learning enabled reflective coded aperture snapshot spectral imaging
    Yu, Zhenming
    Liu, Diyi
    Cheng, Liming
    Meng, Ziyi
    Zhao, Zhengxiang
    Yuan, Xin
    Xu, Kun
    OPTICS EXPRESS, 2022, 30 (26): : 46822 - 46837
  • [49] Deep plug-and-play priors for spectral snapshot compressive imaging
    SIMING ZHENG
    YANG LIU
    ZIYI MENG
    MU QIAO
    ZHISHEN TONG
    XIAOYU YANG
    SHENSHENG HAN
    XIN YUAN
    Photonics Research, 2021, 9 (02) : 18 - 29
  • [50] Snapshot spectral compressive imaging reconstruction using convolution and contextual Transformer
    LISHUN WANG
    ZONGLIANG WU
    YONG ZHONG
    XIN YUAN
    Photonics Research, 2022, (08) : 1848 - 1858