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Proceedings Paper

Predicting the visibility of dynamic DCT distortions in natural videos
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Paper 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.

Paper Details

Date Published: 22 September 2015
PDF: 13 pages
Proc. SPIE 9599, Applications of Digital Image Processing XXXVIII, 959910 (22 September 2015); doi: 10.1117/12.2188460
Show Author Affiliations
Jeremy P. Evert, Southwestern Oklahoma State Univ. (United States)
Md Mushfiqul Alam, Oklahoma State Univ. (United States)
Damon M. Chandler, Shizuoka Univ. (Japan)

Published in SPIE Proceedings Vol. 9599:
Applications of Digital Image Processing XXXVIII
Andrew G. Tescher, Editor(s)

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