Deterministic techniques for multichannel blind image deconvolution
In this paper, we address four deterministic methods for blind multichannel identification in a blind image restoration fr amework. These methods are: SubSpace method (SS), Minimum Noise Subspace (MNS) and Symmetric MNS (SMNS) methods, Cross Relation method (CR) and Least Squares Smoothing method (LSS). The latter is a new method that is introduced, here, for the first time, as an extension, from the 1-D to the 2-D case, of the least squares method by L. Tong et al. (1999). For each method, we detail its basic principle and provide a summary of its corresponding algorithm. In the noise free case, all the methods developed here offer a perfect channel identification. In the noisy case, these methods hav e a different behavior and their performance are compared in terms of channel identification by means of MSE.