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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