Block arithmetic coding for source compression

We introduce “Block Arithmetic Coding” (BAC), a technique for entropy coding that combines many of the advantages of ordinary stream arithmetic coding with the simplicity of block codes. The code is variable length in to fixed out (V to F), unlike Huffman coding which is fixed in to variable out (F to V). We develop two versions of the coder: 1) an optimal encoder based on dynamic programming arguments, and 2) a suboptimal heuristic based on arithmetic coding. The optimal coder is optimal over all V to F complete and proper block codes. We show that the suboptimal coder achieves compression that is within a constant of a perfect entropy coder for independent and identically distributed inputs. BAC is easily implemented, even with large codebooks, because the algorithms for coding and decoding are regular. For instance, codebooks with 2³² entries are feasible. BAC also does not suffer catastrophic failure in the presence of channel errors. Decoding errors are confined to the block in question. The encoding is in practice reasonably efficient. With i.i.d. binary inputs with P(1)=0.95 and 16 bit codes, entropy arguments indicate at most 55.8 bits can be encoded; the BAC heuristic achieves 53.0 and the optimal BAC achieves 53.5. Finally, BAC appears to be much faster than ordinary arithmetic coding