A practical approach to spectral calibration of short wavelength infrared hyper-spectral imaging systems

被引:2
|
作者
Buermen, Miran [1 ]
Pernus, Franjo [1 ]
Likara, Bostjan [1 ]
机构
[1] Univ Ljubljana, Fac Elect Engn, Lab Imaging Technol, Ljubljana 1000, Slovenia
关键词
Short-wavelength infrared; spectroscopy; hyper-spectral imaging; calibration; AOTF; ACOUSTOOPTIC TUNABLE FILTER;
D O I
10.1117/12.841866
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Near-infrared spectroscopy is a promising, rapidly developing, reliable and noninvasive technique, used extensively in the biomedicine and in pharmaceutical industry. With the introduction of acousto-optic tunable filters (AOTF) and highly sensitive InGaAs focal plane sensor arrays, real-time high resolution hyper-spectral imaging has become feasible for a number of new biomedical in vivo applications. However, due to the specificity of the AOTF technology and lack of spectral calibration standardization, maintaining long-term stability and compatibility of the acquired hyper-spectral images across different systems is still a challenging problem. Efficiently solving both is essential as the majority of methods for analysis of hyper-spectral images relay on a priori knowledge extracted from large spectral databases, serving as the basis for reliable qualitative or quantitative analysis of various biological samples. In this study, we propose and evaluate fast and reliable spectral calibration of hyper-spectral imaging systems in the short wavelength infrared spectral region. The proposed spectral calibration method is based on light sources or materials, exhibiting distinct spectral features, which enable robust non-rigid registration of the acquired spectra. The calibration accounts for all of the components of a typical hyper-spectral imaging system such as AOTF, light source, lens and optical fibers. The obtained results indicated that practical, fast and reliable spectral calibration of hyper-spectral imaging systems is possible, thereby assuring long-term stability and inter-system compatibility of the acquired hyper-spectral images.
引用
收藏
页数:6
相关论文
共 50 条
  • [31] HYPER-SPECTRAL IMAGING FOR OVERLAPPING PLASTIC FLAKES SEGMENTATION
    Martinez, Guillem
    Aghaei, Maya
    Dijkstra, Martin
    Nagarajan, Bhalaji
    Jaarsma, Femke
    van de Loosdrecht, Jaap
    Radeva, Petia
    Dijkstra, Klaas
    2022 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP, 2022, : 2331 - 2335
  • [32] Hyper-Spectral Speckle Imaging for Space Situational Awareness
    Hall, Ryan
    Jefferies, Stuart M.
    JOURNAL OF THE ASTRONAUTICAL SCIENCES, 2022, 69 (02): : 581 - 592
  • [33] COMPRESSIVE HYPER-SPECTRAL IMAGING IN THE PRESENCE OF IMPULSE NOISE
    Aggarwal, Hemant Kumar
    Tariyal, Snigdha
    Majumdar, Angshul
    2015 7TH WORKSHOP ON HYPERSPECTRAL IMAGE AND SIGNAL PROCESSING: EVOLUTION IN REMOTE SENSING (WHISPERS), 2015,
  • [34] Combined optical coherence tomography and hyper-spectral imaging
    Attendu, Xavier
    Guay-Lord, Robin
    Strupler, Mathias
    Godbout, Nicolas
    Boudoux, Caroline
    MULTIMODAL BIOMEDICAL IMAGING XII, 2017, 10057
  • [35] Target Discrimination via Hyper-spectral Imaging and Spectral Generalized Angle Analysis
    Chen, Yuheng
    Zhou, Jiankang
    Chen, Xinhua
    Ji, Yiqun
    Shen, Weimin
    TENTH INTERNATIONAL CONFERENCE ON DIGITAL IMAGE PROCESSING (ICDIP 2018), 2018, 10806
  • [36] COMPRESSIVE HYPER-SPECTRAL IMAGING IN THE PRESENCE OF REAL NOISE
    Aggarwal, Hemant Kumar
    Majumdar, Angshul
    2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2016, : 4371 - 4374
  • [37] Hyper-Spectral Speckle Imaging for Space Situational Awareness
    Hall, Ryan
    Jefferies, Stuart M.
    Journal of the Astronautical Sciences, 2022, 69 (02): : 581 - 592
  • [38] Detection of Waxed Chestnuts using Visible and Near-Infrared Hyper-spectral Imaging
    Li, Baicheng
    Hou, Baolu
    Zhou, Yao
    Zhao, Mantong
    Zhang, Dawei
    Hong, Ruijin
    FOOD SCIENCE AND TECHNOLOGY RESEARCH, 2016, 22 (02) : 267 - 277
  • [39] Near-infrared hyper-spectral imaging system for lung tissue malignancy quantization
    Kim, C.
    Lee, J. H.
    BASIC & CLINICAL PHARMACOLOGY & TOXICOLOGY, 2019, 125 : 26 - 26
  • [40] Visible and Near-Infrared Hyper-Spectral Imaging for the Identification of the Type of Wax on Pears
    Li, Baicheng
    Zhou, Yao
    Zhao, Mantong
    Hou, Baolu
    Zhang, Dawei
    Wang, Qi
    Huang, Yuanshen
    JOURNAL OF FOOD PROCESSING AND PRESERVATION, 2017, 41 (01)