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Optics Express

Optics Express

  • Editor: C. Martijn de Sterke
  • Vol. 19, Iss. 16 — Aug. 1, 2011
  • pp: 15173–15180

Robustness of analyses of imaging data

Christian Nansen  »View Author Affiliations

Optics Express, Vol. 19, Issue 16, pp. 15173-15180 (2011)

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Successful classifications of reflectance and vibrational data are to a large extent dependent upon robustness of input data. In this study, a well-known geostatistical approach, variogram analysis, was described and its robustness was assessed through comprehensive evaluation of 3,200 variogram settings. High-resolution hyperspectral imaging data were acquired from greenhouse maize plants, and the robustness (radiometric repeatability) of three variogram parameters (nugget, sill, and range) was examined when generated from imaging data collected from two different sets of plants and with imaging data collected on seven different days in two years. Robustness of variogram parameters was compared with average reflectance values in six spectral bands, three standard vegetation indices (NDVI, SI, and PRI), and PCA scores from principal component analysis.

© 2011 OSA

OCIS Codes
(100.0100) Image processing : Image processing
(100.2960) Image processing : Image analysis
(280.0280) Remote sensing and sensors : Remote sensing and sensors
(150.1135) Machine vision : Algorithms

ToC Category:
Image Processing

Original Manuscript: May 2, 2011
Revised Manuscript: June 28, 2011
Manuscript Accepted: June 29, 2011
Published: July 22, 2011

Christian Nansen, "Robustness of analyses of imaging data," Opt. Express 19, 15173-15180 (2011)

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