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In this paper, we address the problem of unsupervised detection of anomalies in hyperspectral images. Our proposed method is based on a novel statistical background modeling approach that combines local and global approaches and does not assume Gaussianity. The local-global background model has the ability to adapt to all nuances of the background process, like local models, but avoids overfitting...
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