New prediction schemes for lossless coding of fullband and subband images
This paper presents a study of lossless image compression of fullband and subband images using predictive coding. The performance of a number of different fixed and adaptive predictors are evaluated to establish the relative performance of different predictors at various resolutions and to give an indication of the achievable image resolution for given bit rates. In particular, the median adaptive predictor is compared with two new classes of predictors proposed in this paper. One is based on the weighted median filter, while the other uses context modelling to select the optimum from a set of predictors. A graphical tool is also proposed to analyse the prediction methods. Simulations of the different predictors for a variety of real world and medical images, evaluated both numerically and graphically, show the superiority of median based prediction over this proposed implementation of context model based prediction, for all resolutions. The effects of different subband decomposition techniques are also explored.
lossless image compression median filter subband coding dpcm