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Invariant Mixture Recognition in Hyperspectral Images

Pei-hsiu Suen, Glenn Healey
ICCV 2001 pp. 262-267
doi:10.1109/ICCV.2001.10033 /iccv/2001/suen2001iccv-invariant/

Abstract

We present an algorithm for identifying linear mixtures of a specified set of materials in 0.4-2.5 /spl mu/m airborne imaging spectrometer data. The algorithm is invariant to the illumination and atmospheric conditions and the relative amounts of the specified materials within a pixel. Only the spectral reflectance functions for the specified materials are required by the algorithm. Invariance over illumination and atmosphere conditions is achieved by incorporating a physical model for scene variability in the constrained optimization formulation. The algorithm also computes estimates of the amounts of the specified materials in identified mixtures. We demonstrate the effectiveness of the algorithm using real and synthetic HYDICE imagery acquired over a range of conditions and altitudes.

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Cite

Text

Suen and Healey. "Invariant Mixture Recognition in Hyperspectral Images." IEEE/CVF International Conference on Computer Vision, 2001. doi:10.1109/ICCV.2001.10033

Markdown

[Suen and Healey. "Invariant Mixture Recognition in Hyperspectral Images." IEEE/CVF International Conference on Computer Vision, 2001.](https://mlanthology.org/iccv/2001/suen2001iccv-invariant/) doi:10.1109/ICCV.2001.10033

BibTeX

@inproceedings{suen2001iccv-invariant,
  title     = {{Invariant Mixture Recognition in Hyperspectral Images}},
  author    = {Suen, Pei-hsiu and Healey, Glenn},
  booktitle = {IEEE/CVF International Conference on Computer Vision},
  year      = {2001},
  pages     = {262-267},
  doi       = {10.1109/ICCV.2001.10033},
  url       = {https://mlanthology.org/iccv/2001/suen2001iccv-invariant/}
}