Abstract
An new pixel unsupervised hyperspectral image (HSI) segmentation method is proposed. It relies on a binary incoding of spectral reflectance curve variations of pixels that allows to consider HSI segmentation as a clustering problem in the feature set of binary strings. Using a generalized Hamming distance, a k-modes algorithm is applied to obtain a cluster partionning of the HSI with no use of any spatial information.
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