Noise-Adjusted Principal Component Analysis for Buried Radioactive Target Detection and Classification

@article{Du2010NoiseAdjustedPC,
  title={Noise-Adjusted Principal Component Analysis for Buried Radioactive Target Detection and Classification},
  author={Qian Du and Wei Wei and Daniel May and Nicolas H. Younan},
  journal={IEEE Transactions on Nuclear Science},
  year={2010},
  volume={57},
  pages={3760-3767}
}
We present a noise-adjusted principal component analysis (NAPCA)-based approach to the detection and classification of buried radioactive targets with short sensor dwell time. The data used in the experiments is the gamma spectroscopy collected by a Sodium Iodide (NAI) scintillation detector. Spectral transformation methods are first applied to the data, followed by NAPCA. Then k-nearest neighbor (kNN) clustering is applied to the NAPCA-transformed feature subspace to achieve detection or… CONTINUE READING
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