Interference and noise-adjusted principal components analysis

@article{Chang1999InterferenceAN,
  title={Interference and noise-adjusted principal components analysis},
  author={Chien-I Chang and Qian Du},
  journal={IEEE Trans. Geoscience and Remote Sensing},
  year={1999},
  volume={37},
  pages={2387-2396}
}
The goal of principal components analysis (PCA) is to find principal components in accordance with maximum variance of a data matrix. However, it has been shown recently that such variance-based principal components may not adequately represent image quality. As a result, a modified PCA approach based on maximization of SNR was proposed. Called maximum noise fraction (MNF) transformation or noise-adjusted principal components (NAPC) transform, it arranges principal components in decreasing… CONTINUE READING
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