Multistage adaptive prediction using local area based predictor evaluation

An efficient and robust approach to adaptive prediction is presented which uses a local causal area to evaluate a number of individual fixed sub-predictors. Various schemes are proposed to utilise this information, including a rank-order based approach, a two stage adaptive selection technique utilising median filtering, a technique for adaptive combination and a technique incorporating adaptive selection followed by adaptive combination. The respective selection and combination schemes display superior results for particular image types which, coupled with prediction error feedback and adaptive arithmetic coding, produce results superior to CALIC. To produce a more robust predictor a secondary stage based on one of the proposed selection schemes is applied resulting in an adaptive prediction scheme which effectively utilises the principles of predictor combination and selection