Multichannel Bussgang algorithm for blind restoration of natural images

This work addresses the multichannel Bussgang restoration algorithm for blind image deconvolution problems. The case of spatial correlated nonGaussian images is considered, and the structure of nonlinear minimum mean square error estimators, to be used in the Bussgang deconvolution algorithm, is discussed. In particular, it is conjectured that, for nonGaussian, spatially correlated random fields, a better nonlinear estimator is obtained in a suitable wavelet transformed domain. The wavelet transform here considered is the so-called circular harmonic wavelet (CHW), because of its characteristic property of capturing specific image features, such as edges, lines, forks, crosses, and so on. Experimental results pertaining to restoration of motion blurred natural images are also reported.