Joint interpolation, motion and parameter estimation for image sequences with missing data

This paper presents a new scheme for interpolation of missing data in image sequences, an important problem in many areas including archived motion picture film and digital video. A unified framework for image data modelling and motion estimation is adopted which is based on 3-dimensional autoregressive (3DAR) models with motion correction. A fully Bayesian methodology is implemented using the Gibbs Sampler, a method which allows for joint estimation with respect to all of the unknowns, including the motion field.