Lossless image coding via adaptive Takagi-Sugeno fuzzy neural network predictor

With the improvement of the digital system and the development of the Internet, the quality of the multimedia data which includes image, voice and video becomes more and more, so the data compression becomes important. This paper proposed an adaptive Takagi-Sugeno fuzzy neural network (TFNN) system on the data compression technology. The TFNN is applied to be a predictor for differential pulse code modulation (DPCM) of images compression. The TFNN predictor can not only have accurate prediction, but also rather study and adapt to various and constant changing data. A through comparison with the most advanced methods in the literatures highlight the advantages of the proposed adaptive TFNN scheme to data compression.