Institute for Data Analysis and Visualization

Arithmetic coding achieves a superior coding rate when encoding a binary source, but its lack of speed makes it an inferior choice when true high-performance encoding is needed. We present our work on a practical implementation of fast entropy coders for binary messages utilizing only bit shifts and table lookups. To limit code table size we limit our code lengths with a type of variable-to-variable (VV) length code created from source string merging. We refer to these codes as merged codes. With merged codes it is possible to achieve a desired level of speed by adjusting the number of bits read from the source at each step. The most efficient merged codes yield a coder with a worst-case inefficiency of 0.4%, relative to the Shannon entropy. Using a hybrid Golomb-VV Bin Coder we are able to achieve a compression ratio that is competitive with other state-of-the-art coders, at a superior throughput.