M. Haindl and S. imberov (Czech Republic)
Image Restoration, Causal Autoregressive Model
We present a novel multiimage restoration method based on the underlying spatial probabilistic image model for as tronomical image restoration if degradation obeys a lin ear degradation model with the unknown possibly non homogeneous point-spread function. The method assumes that for every ideal undegraded unobservable image sev eral degraded observed images are available. Pixels in the vicinity of image steep discontinuities are left unrestored to minimise restoration blurring effect. The degraded image is assumed to follow a causal simultaneous multidimensional regressive model which leads to an adaptive fast recursive restoration filter. The unknown point-spread function is es timated using the local least-square estimate.
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