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17 September 2018 Using video quality metrics for something other than compression
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Abstract
The development of video quality metrics and perceptual video quality metrics has been a well established pursuit for more than 25 years. The body of work has been seen to be most relevant for improving the performance of visual compression algorithms. However, modeling the human perception of video with an algorithm of some sort is notoriously complicated. As a result the perceptual coding of video remains challenging and no standards have incorporated perceptual video quality metrics within their specification. In this paper we present the use of video metrics at the system level of a video processing pipeline. We show that it is possible to combine the artefact detection and correction process by posing the problem as a classification exercise. We also present the use of video metrics as part of a classical testing pipeline for software infrastructure, but here it is sensitive to the perceived quality in picture degradation.
Conference Presentation
© (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Anil Kokaram, Damien Kelly, Sasi Inguva, Jessie Lin, Yilin Wang, Chao Chen, Neil Birkbeck, Michele Covell, Balu Adsumilli, and Steve Benting "Using video quality metrics for something other than compression", Proc. SPIE 10752, Applications of Digital Image Processing XLI, 107520T (17 September 2018); https://doi.org/10.1117/12.2322506
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