Essential processing methods of hyperspectral images of agricultural and food products
作者: Beibei JiaWei WangXinzhi NiKurt C. LawrenceHong ZhuangSeung-Chul YoonZhixian Gao
作者单位: 1College of Engineering, China Agricultural University, Beijing, 100083, China
2Crop Genetics and Breeding Research Unit, USDA-ARS, 2747 Davis Road, Tifton, GA, 31793, USA
3Quality & Safety Assessment Research Unit, USDA-ARS, Athens, GA, 30605, USA
4Tianjin Key Laboratory of Risk Assessment and Control Technology for Environment and Food Safety, Tianjin Institute of Health and Environment Medicine, Tianjin, 300050, China
刊名: Chemometrics and Intelligent Laboratory Systems, 2020, Vol.198
来源数据库: Elsevier Journal
DOI: 10.1016/j.chemolab.2020.103936
关键词: Hyperspectral imagePre-processing methodUneven illuminationPost-processing methodDistribution maps
英文摘要: Abstract(#br)Hyperspectral images integrate spatial and spectral details together. They can provide valuable information about both external physical and internal chemical characteristics of agricultural and food products rapidly and non-destructively. Despite rapid improvements in instruments and acquisition techniques, the collected high-quality hyperspectral images still contain much useless information, like uneven illumination, background, specular reflection, and bad pixels that need to be removed. That is, hyperspectral image preprocessing is necessary for almost each hyperspectral image to get pure images or pixels, or to reduce negative influences on the subsequent detection, classification, and prediction analysis. This manuscript will enumerate some possible solutions to deal...
全文获取路径: Elsevier  (合作)

  • processing 加工
  • products 制品
  • agricultural 农业的