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22 September 2015 Predicting the visibility of dynamic DCT distortions in natural videos
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Abstract
Compression has enabled years of exponential growth in global video consumption, providing video everywhere, with few perceptible artifacts. Automated Video Quality Assessment (VQA) is an enabler of compression. We present data showing video contrast affects on artifact visibility. Based on our data, we propose a contrast-gain-control VQA algorithm, with target spatiotemporal property weighting, and using our data to tune existing VQA algorithms for improved artifact threshold predictions. This paper provides much needed data on natural video mask contrast and artifact visibility, and provides important insights for how VQA algorithms can be improved to better predict video quality in the high-quality regime.
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Jeremy P. Evert, Md Mushfiqul Alam, and Damon M. Chandler "Predicting the visibility of dynamic DCT distortions in natural videos", Proc. SPIE 9599, Applications of Digital Image Processing XXXVIII, 959910 (22 September 2015); https://doi.org/10.1117/12.2188460
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