Image blind separation based on sparse change
A blind source separation and sparse transformation technology, applied in the field of image noise reduction, can solve the problems that restrict the performance of image blind source separation methods, and cannot effectively describe two-dimensional or high-Vitch heterogeneous information.
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[0040] A preferred embodiment of the present invention is described as follows in conjunction with accompanying drawing:
[0041] This image blind source separation method based on sparse transformation, such as figure 1shown. First, use the contour wavelet transform Contourlet to perform multi-scale and multi-directional sparse decomposition of the received mixed image signal, and use the sparsity criterion in the contour wavelet transform Contourlet domain to select the sub-image group with the best sparsity; then use the traditional The fast fixed-point independent component analysis method blindly separates the selected sub-image group to obtain the separation matrix; finally, use this separation matrix to separate the received mixed image signal, extract each independent component in the mixed image, and achieve the image blind source purpose of separation.
[0042] The specific steps are:
[0043] ①Initialize settings. Set the Laplastian decomposition LP decompositio...
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