An early CU partition mode decision algorithm in VVC based on variogram for virtual reality 360 degree videos

Abstract

Abstract360-degree videos have become increasingly popular with the application of virtual reality (VR) technology. To encode such kind of videos with ultra-high resolution, an efficient and real-time video encoder becomes a key requirement. The Versatile Video Coding (VVC) standard has good coding performance. However, it has pretty high computational complexity which increasing the application cost of 360-degree videos. Among them, the decision of the quadtree with nested multi-type tree (QTMT) partitioning structure is one of the time-consuming procedures. In this paper, based on the characteristics of 360-degree video with Equirectangular projection (ERP) format, the empirical variogram combined with Mahalanobis distance is introduced to measure the difference between the horizontal and vertical directions of the CU, and a fast partition algorithm is proposed. The experimental results show that the algorithm saves 32.13% of the coding time with only an increase of 0.66% in BDBR.

Extreme Learning Machine-Enabled Coding Unit Partitioning Algorithm for Versatile Video Coding

“…The method includes a swift quadtree decision approach (FQD) and a prompt multi-type tree decision method (FMD). Zhang et al propose an efficient partition algorithm by introducing the empirical variogram along with Mahalanobis distance to quantify the disparity between the horizontal and vertical directions of the coding unit [18].…”