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An overview of regression methods in hyperspectral and multispectral imaging

Publikation: Bidrag til bog/antologi/rapportBidrag til bog/antologiForskningfagfællebedømt

  • 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.

OriginalsprogEngelsk
TitelHyperspectral Imaging
RedaktørerJosé Manuel Amigo
Antal sider26
ForlagElsevier
Publikationsdato2020
Sider205-230
Kapitel2.8
ISBN (Trykt)978-0-444-63977-6
DOI
StatusUdgivet - 2020
NavnData Handling in Science and Technology
Vol/bind32
ISSN0922-3487

ID: 230849559