A Fast Sample Adaptive Offset Algorithm for 360∘ Video

Abstract

The increased demand for virtual reality brings more challenges to 360∘ video coding. 360∘ video needs to be projected as a planar video before encoding. This process will produce projection distortion. The degree of projection distortion depends on the location of the pixel. Traditional coding algorithms cannot respond to this feature efficiently enough. In this paper, a fast Sample Adaptive Offset (SAO) algorithm for 360∘ video is proposed. The proposed algorithm improves the SAO process. On the basis of retaining the whole SAO process, a simplified SAO process is added. First, the coding tree unit (CTU) of performing the simplified SAO process is filtered according to the rate distortion cost (RD-cost) of the intra- or inter-prediction and the location of the CTU. Subsequently, the CTU is sampled at intervals according to the equirectangular projection (ERP) characteristics, and the CTU of performing the simplified SAO process is determined. Experimental results show that the proposed algorithm achieves 60% time of SAO process reduction, with only 0.29% luma Bjontegaard delta rate (BD-rate) increases on average.