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Locality and label information of training samples play an important role in image classification. However, previous dictionary learning algorithms do not take the locality and label information of atoms into account together in the learning process, and thus their performance is limited. In this paper, a discriminative dictionary learning algorithm, called the localityconstrained and label embedding dictionary learning (LCLE-DL) algorithm, was proposed for image classification. First, thedoi:10.1109/tnnls.2015.2508025 pmid:28055916 fatcat:u5jf6eugvfaszgxxyxdoth22zq