Blind signal separation and identification of mixtures of images

In this paper, a novel technique for blind signal separation based on a combination of second order and higher order approaches is introduced. The problem of blind signal separation was solved in a wavelet domain. The main idea behind this approach is that the mixing signal can be decomposed into a sum of uncorrelated and/or independent sub-bands using the wavelet transform. In the beginning, the observed signal is prewhitened in the time domain then, the initial separation matrix will be estimated from second order statistics decorrelation method in the wavelet domain. The estimating matrix will be used as an initial separating matrix in the higher order statistics method in order to estimate the final separation matrix. The algorithm was tested using natural images. Extensive experiments have confirmed that the use of the proposed procedure provides promising results in separating the image from noisy mixtures of images.