Memory-efficient semi-quasi renormalization for arithmetic coding

We propose a highly efficient, look-up table-based, renormalization method that can be used by any binary arithmetic encoder with the follow-on procedure. It replaces the time-consuming branching operations in the renormalization process with table look-ups and some simple bit-wise operations. We show that our new renormalization method outperforms the currently used ones with much less memory requirement than the previously known, table-based quasi-coder.