A novel method of separating the point spread function from blurred images using zeros of the Z transform is presented when more than one blurred image is available. The proposed method is demonstrated to be effective with significant contamination with signal-to-noise ratios of over 30 dB. This method holds much promise as a blind deconvolution (i.e. problem of recovering two functions from their convolution) technique, as it does not impose any constraints on the point spread function, such as positivity. The article is presented with experimental results over different signal-to-noise ratios, depicting its effectiveness as a practical image restoration technique.
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