The goal of the blind source separation (BSS) is to recover independent sources from the sensor observation which are unknown linear mixtures of the unobserved source signals. In contrast to correlation-based transformation such as the principal component analysis, the blind techniques not only decorrelate the signals (second-order statistics) but also reduce higher-order dependencies, attempting to make the signals as independent as possible. In this paper we introduce the BSS algorithms with the emphasis on applications in image processing. Computer simulations illustrate and confirm the usefulness and performance of the discussed algorithms.
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