Adaptive Wavelet-based-CMAC Network Predictor Design for Lossless Image Coding

In this paper, we propose a novel wavelet-based-CMAC (WCMAC) network for predictive image coding. The Gaussian functions of traditional CMAC are replaced by wavelet functions. In addition, properties and advantages of fuzzy TSK-model are used to modify the activation functions of CMAC for obtaining high approximation accuracy and convergent rate. The WCMAC is employed to predict differential pulse code modulation (DPCM) of image compression. The WCMAC predictor can not only have accurate prediction, but also rather study and adapt to various and constant changing data. Experimental results and comparisons with other state-of-the-art lossless predictors are given to highlight the advantages of the proposed approach.