Continuous wavelet transformations for hyperspectral feature detection

  • J.G. Ferwerda*
  • , Simon D. Jones
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Abstract

A novel method for the analysis of spectra and detection of absorption features in hyperspectral signatures is proposed, based on the ability of wavelet transformations to enhance absorption features. Field spectra of wheat grown on different levels of available nitrogen were collected, and compared to the foliar nitrogen content. The spectra were assessed both as absolute reflectances and recalculated into derivative spectra, and their respective wavelet transformed signals. Wavelet transformed signals, transformed using the Daubechies 5 motherwavelet at scaling level 32, performed consistently better than reflectance or derivative spectra when tested in a bootstrapped phased regression against nitrogen.

Original languageEnglish
Title of host publicationProgress in Spatial Data Handling - 12th International Symposium on Spatial Data Handling, SDH 2006
Pages167-178
Number of pages12
DOIs
Publication statusPublished - 2006
Externally publishedYes
Event12th International Symposium on Spatial Data Handling, SDH 2006 - Vienna, Austria
Duration: 12 Jul 200614 Jul 2006

Publication series

NameProgress in Spatial Data Handling - 12th International Symposium on Spatial Data Handling, SDH 2006

Conference

Conference12th International Symposium on Spatial Data Handling, SDH 2006
Country/TerritoryAustria
CityVienna
Period12/07/0614/07/06

Keywords

  • ITC-CV

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