Real-time anomaly detection in hyperspectral images using multivariate normal mixture models and GPU processing

@article{Tarabalka2008RealtimeAD,
  title={Real-time anomaly detection in hyperspectral images using multivariate normal mixture models and GPU processing},
  author={Yuliya Tarabalka and Trym Vegard Haavardsholm and Ingebj{\o}rg K{\aa}sen and Torbj{\o}rn Skauli},
  journal={Journal of Real-Time Image Processing},
  year={2008},
  volume={4},
  pages={287-300}
}
Hyperspectral imaging, which records a detailed spectrum of light arriving in each pixel, has many potential uses in remote sensing as well as other application areas. Practical applications will typically require real-time processing of large data volumes recorded by a hyperspectral imager. This paper investigates the use of graphics processing units (GPU) for such real-time processing. In particular, the paper studies a hyperspectral anomaly detection algorithm based on normal mixture… CONTINUE READING

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