Parallelization of Context-Based Adaptive Binary Arithmetic Coders

Abstract

This paper presents novel approaches to parallelize context-based adaptive binary arithmetic coders (CABACs). Two new parallelized CABACs (or PCABACs) are presented and the methods described. These coders are designed by modifying commonly used binary multiplication-free arithmetic coders. One utilizes linear approximation and simplifies the hardware by assuming that the less probable symbol probability is almost the same while performing the en/decoding (referred to as QL-coder). Another codec applies table lookup technique and achieves parallelism with a parallelized probability model (referred to as QT-coder). QL-coder is improved from the IBM Q-coder, and the QT-coder is improved from the CABAC used in H.264 video compression standard. Throughput, in both coders, is significantly increased after parallelization. A fast interval search method is also proposed