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In this paper, a fresh procedure to handle image mixtures by means of blindsignal separation relying on a combination of second order and higher orderstatistics techniques are introduced. The problem of blind signal separation isreassigned to the wavelet domain. The key idea behind this method is that theimage mixture can be decomposed into the sum of uncorrelated and/or independentsub-bands using wavelet transform. Initially, the observed image ispre-whitened in the space domain. Afterwards, an initial separation matrix isestimated from the second order statistics de-correlation model in the waveletdomain. Later, this matrix will be used as an initial separation matrix for thehigher order statistics stage in order to find the best separation matrix. Thesuggested algorithm was tested using natural images.Experiments have confirmedthat the use of the proposed process provides promising outcomes in identifyingan image from noisy mixtures of images.

Blind signal separation and identification of mixtures of images