Fast and Efficient Compression of Floating-Point Data
IEEE Transactions on Visualization and Computer Graphics
EURASIP Journal on Applied Signal Processing
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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 andtable lookups. To limit code table size we limit our code lengths with a typeof variable-to-variable (VV) length code created from source string merging.We refer to these codes as "merged codes". With merged codes it is possibleto achieve a desired level of speed by adjusting the number of bits read fromthe source at each step. The most efficient merged codes yield a coder witha worst-case inefficiency of 0.4%, relative to the Shannon entropy. Using ahybrid Golomb-VV Bin Coder we are able to achieve a compression ratio thatis competitive with other state-of-the-art coders, at a superior throughput.