CuSAO: Parallel Optimization of Sample Adaptive Offset (SAO) for Video Encoder

Conventional SAO module in encoder decides classification mode and offsets based on the statistical data of pixels for accuracy. It needs to traverse all pixels several times, which is extremely time-consuming. All improving works for efficiency either reduce statistical data or concentrate only on SAO decoder. To tackle this, a fast parallel algorithm for standard SAO in encoder named CuSAO based on Graphics Processing Unit (GPU) is proposed. We proposed a pixel grid – thread mapping method and adopted parallel computing of multi-granularity in different stages of SAO encoder. Experimental results demonstrate our method outperforms state-of-the-arts modules and shows impressive results in terms of efficiency, reaching a significant time saving by average 75% and up to more than 85%