Abstract
An important topic in image restoration is interpolation of missing data in image sequences. Missing data is a result of dirt on film and of ageing processes where the film contents are replaced by data that bears little relationship with the original scene. We present a method for interpolating missing data with the aim of achieving higher fidelity and more consistency in the interpolated results than can be achieved by existing methods. This is done by combining autoregressive models and Markov-random field techniques. Experimental results confirm the superior performance of the proposed method over existing methods.
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