A Fast Sample Adaptive Offset Algorithm for 360∘ Video

Author:

Zhang Mengmeng1,Su Renbo1,Liu Zhi1ORCID,Mao Fuqi1,Yue Wen2

Affiliation:

1. North China University of Technology, Beijing 100144, P. R. China

2. China University of Geosciences, Beijing 100083, P. R. China

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.

Funder

National Natural Science Foundation of China

Beijing Municipal Natural Science Foundation

Great Wall Scholar Project of Beijing Municipal Education Commission

Beijing Youth Talent Project

Beijing Municipal Education Commission General Program

Publisher

World Scientific Pub Co Pte Lt

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

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