Hyperspectral near infrared image calibration and regression

Mikko Mäkelä*, Paul Geladi, Marja Rissanen, Lauri Rautkari, Olli Dahl

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

2 Citations (Scopus)
51 Downloads (Pure)

Abstract

Reference materials are used in diffuse reflectance imaging for transforming the digitized camera signal into reflectance and absorbance units for subsequent interpretation. Traditional white and dark reference signals are generally used for calculating reflectance or absorbance, but these can be supplemented with additional reflectance targets to improve the accuracy of reflectance transformations. In this work we provide an overview of hyperspectral image regression and assess the effects of reflectance calibration on image interpretation using partial least squares regression. Linear and quadratic reflectance transformations based on additional reflectance targets decrease average measurement errors and make it easier to estimate model pseudorank during image regression. The lowest measurement and prediction errors were obtained with the column and wavelength specific quadratic transformations which retained the spatial information provided by the line-scanning instrument and reduced errors in the predicted concentration maps.

Original languageEnglish
Pages (from-to)56-63
Number of pages8
JournalAnalytica Chimica Acta
Volume1105
DOIs
Publication statusPublished - 8 Apr 2020
MoE publication typeA1 Journal article-refereed

Keywords

  • Hyperspectral imaging
  • Partial least squares
  • Prediction
  • Pseudorank
  • Reflectance calibration
  • Textile analysis

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