Video compression with parallel processing
Parallel Computing - Parallel computing in image and video processing
Hierarchical Parallelization of an H.264/AVC Video Encoder
PARELEC '06 Proceedings of the international symposium on Parallel Computing in Electrical Engineering
A Highly Efficient Parallel Algorithm for H.264 Encoder Based on Macro-Block Region Partition
HPCC '07 Proceedings of the 3rd international conference on High Performance Computing and Communications
Adaptive slice-level parallelism for H.264/AVC encoding using pre macroblock mode selection
Journal of Visual Communication and Image Representation
Hexagon-based search pattern for fast block motion estimation
IEEE Transactions on Circuits and Systems for Video Technology
Overview of the H.264/AVC video coding standard
IEEE Transactions on Circuits and Systems for Video Technology
Design and implementation of parallel video encoding strategies using divisible load analysis
IEEE Transactions on Circuits and Systems for Video Technology
A Novel Macro-Block Group Based AVS Coding Scheme for Many-Core Processor
Journal of Signal Processing Systems
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The slice-level parallelism is popular in parallel video coding. However, the quality loses greatly because the dependency between macro-blocks is broken, especially on many-core platforms. To address this problem, a novel Macro-Block Group (MBG) decomposition scheme is presented for parallel AVS coding. In the proposed scheme, video frames are equally divided into rectangular MBG regions, each consists of more rows and less columns than the slice-level scheme. Since MBG is not supported by AVS, a vertical partitioning scheme is introduced, and the mode confining and MVD adjusting techniques are utilized to keep consistency with the standard. In practice, our parallel encoder is developed on the TILE64 platform, where P/B frames use the MBG-level parallelism and I frames use the macro-block-level parallelism. Experiments show that the proposed scheme can achieve a reduction of 52% (IPPP) and 41% (IBBP) in quality loss while keeping the same speed-up compared with the slice-level parallelism.