Compressed Video Quality Assessment for Super-Resolution: a Benchmark
and a Quality Metric
- URL: http://arxiv.org/abs/2305.04844v1
- Date: Mon, 8 May 2023 16:42:55 GMT
- Title: Compressed Video Quality Assessment for Super-Resolution: a Benchmark
and a Quality Metric
- Authors: Evgeney Bogatyrev, Ivan Molodetskikh and Dmitriy Vatolin
- Abstract summary: We developed a super-resolution benchmark to analyze SR's capacity to upscale compressed videos.
We assessed 17 state-ofthe-art SR models using our benchmark and evaluated their ability to preserve scene context.
We also developed an objective-quality-assessment metric based on the current best objective metrics.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: We developed a super-resolution (SR) benchmark to analyze SR's capacity to
upscale compressed videos. Our dataset employed video codecs based on five
compression standards: H.264, H.265, H.266, AV1, and AVS3. We assessed 17
state-ofthe-art SR models using our benchmark and evaluated their ability to
preserve scene context and their susceptibility to compression artifacts. To
get an accurate perceptual ranking of SR models, we conducted a crowd-sourced
side-by-side comparison of their outputs. The benchmark is publicly available
at
https://videoprocessing.ai/benchmarks/super-resolutionfor-video-compression.html.
We also analyzed benchmark results and developed an
objective-quality-assessment metric based on the current bestperforming
objective metrics. Our metric outperforms others, according to Spearman
correlation with subjective scores for compressed video upscaling. It is
publicly available at
https://github.com/EvgeneyBogatyrev/super-resolution-metric.
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