Transform domain LMS-based adaptive prediction for lossless image coding

Abstract

This paper is concerned with adaptive prediction for lossless image coding. A new predictor is proposed. This predictor involves two major steps: constructing a good predictor for each pixel using the transform domain LMS algorithm and adaptively combining it with a set of fixed predictors. The first step is targeting areas where simple predictors do not perform well, while the second step is an effective method to reduce the modelling costs associated with the uncertainty of the models. When a context-based arithmetic encoder is used to encode the prediction error, the compression performance of the proposed algorithm is better than or comparable to that of other published algorithms.