Blur identification using bispectrum

Blur identification methods based on the bispectrum of an observed noisy and blurred image are proposed. Blur identification is addressed, in the case of uniform blurs, by zero-crossing detection in a particular cross section of the bispectrum of the observed image. The identification of general finite-impulse-response blurs is considered. The blurred image is represented by a nonminimum phase ARMA (autoregressive moving average) model whose parameters are identified using the complex bispectrum of the observed image. These methods are superior to previous methods which are based on the second-order statistics of the image, since the bispectrum is insensitive to additive, Gaussian noise in theory, and it contains the phase of the blur transfer function. Simulation results are provided