M2OVQA: Multi-space signal characterization and multi-channel information aggregation for quality assessment of compressed omnidirectional videos

Abstract

Considering the high requirements for omnidirectional video compression, we propose an objective quality evaluation method to assess quality loss in encoding omnidirectional videos. According to characteristics of 360° videos, we consider multi-space signal characterization (MSSC) to fully characterize the distortions of video signals from spatial/image domains to frequency domains and from image content to motion information, and further consider multi-channel information aggregation (MCIA) to fuse scores from multiple projection planes and temporal divided groups. The main innovation of our method is to establish a universal framework in bridging the connection between typical quality assessment and 360° quality assessment to measure 360° video quality effectively and efficiently. Experimental results show that our method outperforms state-of-the-art 2D quality metrics and quality metrics for omnidirectional images.