Multi-level complexity reduction for HEVC multiview coding

Caoyang Jiang, Michigan Technological University
Saeid Nooshabadi, Michigan Technological University


Standardized in 2014, multiview extension of high efficiency video coding (MV-HEVC) offers significantly better compression performance of up to 50% for multiview and 3D videos compared to multiple independent single view HEVC coding. However, the extreme high computational complexity of MV-HEVC demands significant optimization of the encoder. In this work, we propose a series of optimization techniques at various levels of abstraction: non-aggregation massively parallel motion estimation (ME) and disparity estimation (DE) for prediction units, fractional and bidirectional ME/DE, quantization parameter-based early termination of coding tree unit (CTU), and optimized resource-scheduled wave front parallel processing for CTU. When evaluated over three views for all available official multiview video coding test sequences, proposed optimization outperforms the anchor encoder by average factor of 5.4 at the cost of 4.4% bitrate (DBR) increase at no loss in PSNR, or alternatively a PSNR degradation of 0.12 dB at no change to the DBR.