Adaptive predictor combination and its applications in lossless image coding

Lossless image coding is an essential requirement for medical imaging applications where no information loss is allowed. Lossless image compression techniques usually have two major components: adaptive prediction and adaptive entropy coding. This paper is concerned with adaptive prediction. An overview of a new type of predictor which is an adaptive combination of a set of sub-predictors is presented. The compression performance of the state-of-the-art algorithms such as CALIC and LOCO is compared with that of the algorithms that employ this new type of predictor.