A high throughput CABAC algorithm using syntax element partitioning

Enabling parallel processing is becoming increasingly necessary for video decoding as performance requirements continue to rise due to growing resolution and frame rate demands. It is important to address known bottlenecks in the video decoder such as entropy decoding, specifically the highly serial Context-based Adaptive Binary Arithmetic Coding (CABAC) algorithm. Concurrency must be enabled with minimal cost to coding efficiency, power, area and delay. This work proposes a new CABAC algorithm for the next generation standard in which binary symbols are grouped by syntax elements and assigned to different partitions which can be decoded in parallel. Furthermore, since the distribution of binary symbols changes with quantization, an adaptive binary symbol allocation scheme is proposed to maximize throughput. Application of this next generation CABAC algorithm on five 720p sequences shows a throughput increase of up to 3x can be achieved with negligible impact on coding efficiency (0.06% to 0.37%), which is a 2 to 4x reduction in coding penalty compared with H.264/AVC and entropy slices. Area cost is also reduced by 2x. This increased throughput can be traded-off for low power consumption in mobile applications.