Fast sample adaptive offset algorithm for 360-degree video coding

Abstract 360-degree video is becoming popular with the development of the virtual reality(VR) technology in recent years. For this kind of video, pictures are projected to a two-dimensional plane. Standard video encoders are used for compression. Due to the projection mapping of the spherical video to the two-dimensional plane video, many conventional coding tools can be adjusted properly for better performance. As the 360-degree videos are high resolution videos, usually 8K resolution videos, the high complexity for encoding 360-degree videos is a problem to be solved urgently, especially for the latest video standard H.265/HEVC. Sample adaptive offset (SAO) is a new tool adopted in H.265/HEVC. It can reduce ringing artifacts and achieve higher coding efficiency. But it also introduces high computational complexity, especially on high resolution videos. In this paper, a fuzzy control based fast SAO method is proposed to reduce the high computational complexity in SAO encoding process according to the characteristics of the ERP format video. Compared with the original algorithm in the reference software HM 16.14, experimental results show that the proposed method can reduce about 73% SAO encoding time on average under the common test conditions with negligible loss.