An overview of regression methods in hyperspectral and multispectral imaging

Research output: Chapter in Book/Report/Conference proceedingBook chapterResearchpeer-review

  • Irina Torres
  • José Manuel Amigo

Pixel-wise and bulk-wise quantitation of compounds in surfaces of different nature using hyperspectral and multispectral images is of a major interest, especially in fields like food and pharmaceutical production. This chapter revises the most common linear methods together with a brief overview of nonlinear methods applied in the regression framework from a practical point of view. The main benefits and drawbacks are discussed focused on applications in food and pharmaceutical production. Moreover, precise guidelines are given to develop calibration/regression models.

Original languageEnglish
Title of host publicationHyperspectral Imaging
EditorsJosé Manuel Amigo
Number of pages26
Publication date2020
ISBN (Print)978-0-444-63977-6
Publication statusPublished - 2020
SeriesData Handling in Science and Technology

    Research areas

  • ANN, Food, MLR, PCR, Pharma, PLS, SVM, Validation

ID: 230849559