Title | ||
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M2OVQA: Multi-space signal characterization and multi-channel information aggregation for quality assessment of compressed omnidirectional videos |
Abstract | ||
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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. |
Year | DOI | Venue |
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2022 | 10.1016/j.jvcir.2021.103419 | Journal of Visual Communication and Image Representation |
Keywords | DocType | Volume |
Omnidirectional video quality assessment,Image quality assessment,Compression distortion,Signal characterization,Information aggregation | Journal | 82 |
ISSN | Citations | PageRank |
1047-3203 | 0 | 0.34 |
References | Authors | |
0 | 2 |
Name | Order | Citations | PageRank |
---|---|---|---|
Xiongli Chai | 1 | 8 | 3.17 |
Feng Shao | 2 | 603 | 72.75 |