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Image enhancement via blind decomposition techniques

Unsupervised learning and blind signal decomposition methods are used for recovering unknown source signals from their linear mixtures using the observed data only. In these methods, a new representation of the data can reveal some hidden information inherent in the data. In this study, principal component analysis, independent component analysis and non-negative matrix factorization methodologies are applied on a single image for extracting information and image enhancement.