Video quality analysis framework for spatial and temporal artifacts

Yilin Wang; Balu Adsumilli

doi:10.1117/12.2322328

17 September 2018 Video quality analysis framework for spatial and temporal artifacts

Yilin Wang, Balu Adsumilli

Proceedings Volume 10752, Applications of Digital Image Processing XLI; 1075215 (2018) https://doi.org/10.1117/12.2322328
Event: SPIE Optical Engineering + Applications, 2018, San Diego, California, United States

Abstract

Video quality metrics are essential for improved video processing algorithms. Common video quality metrics are simple averages of independently computed per frame spatial metrics, but human quality perception is not uniform across frames. In particular, the order of frames matter, as does content complexity and scene changes. In this work, we develop a video quality framework that comprehensively integrates both spatial and temporal metrics at three levels: frame, scene, and full video. We experimentally demonstrate improved correlation of spatial metrics with human evaluation as well a new well-correlated temporal metric (jerkiness) based on this framework.

Conference Presentation

Citation Download Citation

Yilin Wang and Balu Adsumilli "Video quality analysis framework for spatial and temporal artifacts", Proc. SPIE 10752, Applications of Digital Image Processing XLI, 1075215 (17 September 2018); https://doi.org/10.1117/12.2322328

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