Adaptive interpolator with context modeling in lifting scheme for lossless coding

Abstract

Adaptive interpolation with double-interpolator is used for image coding. The double-interpolator means that two adaptive prediction stages are used. The outer loop is an adaptive FIR predictor. The inner loop is an texture based bias estimation. The bias means a content dependent estimated prediction error. By assuming the signals to consist of polynomials of various degrees, the predictor of the outer loop is constructed by linearly combining a set of maximally nat filters. The maximally flat filter is the filtering implementation of the Lagrange interpolation. The prediction is done block by block. Within a block, similar with the lifting scheme, a hierarchical multiresolution prediction is used starting from the fewest resolution 2 by 2 sub-block. The least square prediction error criterion is used to derive the weighting coefficients of the predictor. To further reduce the prediction error, an inner loop to estimate the prediction error is included. Within the inner loop, the pixel to be predicted is classified into groups according to the neighborhood condition. The accumulated mean of the prediction errors of all the pixels within the same group is considered as the bias of the prediction error. This bias is then extracted from the actual prediction error to reduce entropy.