MULTIDIMENSIONAL SYSTEM-IDENTIFICATION THROUGH BLIND DECONVOLUTION

By invoking characteristics of the recently introduced zero-sheet of the spectrum of a signal having finite (or compact) support, it is noted that the multidimensional system identification problem should be solvable through blind deconvolution, that is, the system response function should be inferrable in the absence of prior knowledge of the signal which excites the system. It is pointed out that practical blind deconvolution can only be effected iteratively at present. An iterative blind identification algorithm is described and is illustrated by recovery of images from blurred versions contaminated with noise of varying levels. Successful blind deconvolution is achieved without invoking prior knowledge of either the forms or the supports of either the original images or the point spread functions, which respectively correspond to exciting signals and response functions.