Context-based adaptive binary arithmetic coding (cabac) is a single operation mode for entropy coding in the last video coding standard high-efficiency video coding. For high-resolution applications, the throughput of...
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Context-based adaptive binary arithmetic coding (cabac) is a single operation mode for entropy coding in the last video coding standard high-efficiency video coding. For high-resolution applications, the throughput of one bin/cycle is not sufficient and it is a very challenging task to implement pipeline and/or parallel cabac decoding architecture by simply adding more stages. Indeed, the tight data dependencies make it difficult to parallelise and cause it to be a throughput bottleneck for video decoding. Consequently, in order to improve the cabac decoder throughput, parallel and pipeline architectures are used in authors' design. In this work, an algorithm-architecture adequation is proposed to implement a cabacdecoder on a field programmable gate array. Mainly, a new classification of 32 syntax elements is given to speed up the authors' solution. Furthermore, the context selection and modelling of regular syntax elements are studied, designed and implemented. Finally, a novel technique of memories rearrangement to reduce the critical path delay required to process each binary symbol is proposed. As a result, the implementation can process 2.2 bins/cycle when operated at 123.49 MHz and exhibits an improved high-throughput of 271.678 Mbins/s. The hardware architecture is coded using hardware description language and synthesised using ISE Xilinx tools targeting the Virtex4 platform.
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