Abstract
H.264/AVC is the latest video compression standard. It concentrates on video compression and robust transmission support over networks. H.264/AVC could achieve about 60% bit-rate saving over MPEG-2, and about 40% bit-rate saving over MPEG-4 at the same video quality. Because of its high compression efficiency, H.264 attracts high interest for many applications such as High Definition DVD, Digital TV, Digital Camcorders, Internet video streaming, and others. Context-based Adaptive Binary Arithmetic Coding (CABAC) is the entropy coding method used in H.264 main profile. Compare to the Context-based Adaptive Variable Length Coding (CAVLC), CABAC provides a reduction in bit rate about 30%. In this thesis, we propose a fast architecture of the CABAC decoder for residual data. Because the binary arithmetic decoder is the critical part of the CABAC decoder. We perform twice reordering technique to reduce the critical path of the decoding process. The critical path has been successfully shorten from to . In the context modeling stage we propose the caching and pre-fetch methods so that the update and load of the context models can be performed at the same time. Furthermore, we propose an algorithm that makes sure the update of the context models in the pipelining at the correct time and decrease the accessing times. As a result, a fast and simple architecture of the CABAC decoder is proposed. Our design is implemented on Xilinx multimedia board that uses less logic elements and the maximum working frequency is 135 MHz. Because of the less device usage and higher working frequency, it is suitable to be an IP core.