Adaptive arithmetic coding using fuzzy reasoning and grey prediction

Abstract Arithmetic coding is an attractive technique for lossless data compression. The most important thing in arithmetic coding is to construct a good modeler that always provides accurate probability estimation for incoming data. However, the characteristics of various types of source data bear a lot of uncertainty and are hard to be extracted, so we integrate fuzzy logic and grey theory to develop a smart fuzzy-grey-tuning modeler to deal with the problem of probability estimation. The average compression efficiency of the proposed method is better than other lossless compression methods, such as the Huffman, the approximate arithmetic, and the Lempel–Ziv, for three types of source data: text files, image files and binary files. Besides, the design is simple, fast, and suitable for VLSI implementation since an efficient table-look-up approach is adopted.