Multichannel blind blur identification and image restoration

This paper considers the problem of multi-channel blind image restoration and blur identification. By constructing the blind identification problem into an optimization problem, we propose a subspace decomposition based algorithm to blindly identify the blur functions. The proposed algorithm is inherently the same as many of the others in the literature, but at significantly reduced computation complexity. Let M be the number of blurred images available, N1 X N2 be the size of the images and L1 X L2 be the size of blur functions, our algorithm has a computational complexity of O(M2L21L22N1N2), as compared to O(M4L21L22N1N2) for previous works. The proposed algorithm is therefore more suitable for practical applications.