30 March 2015 Spatiotemporal video deinterlacing using control grid interpolation
Author Affiliations +
Abstract
With the advent of progressive format display and broadcast technologies, video deinterlacing has become an important video-processing technique. Numerous approaches exist in the literature to accomplish deinterlacing. While most earlier methods were simple linear filtering-based approaches, the emergence of faster computing technologies and even dedicated video-processing hardware in display units has allowed higher quality but also more computationally intense deinterlacing algorithms to become practical. Most modern approaches analyze motion and content in video to select different deinterlacing methods for various spatiotemporal regions. We introduce a family of deinterlacers that employs spectral residue to choose between and weight control grid interpolation based spatial and temporal deinterlacing methods. The proposed approaches perform better than the prior state-of-the-art based on peak signal-to-noise ratio, other visual quality metrics, and simple perception-based subjective evaluations conducted by human viewers. We further study the advantages of using soft and hard decision thresholds on the visual performance.
© 2015 SPIE and IS&T 1017-9909/2015/$25.00 © 2015 SPIE and IS&T
Ragav Venkatesan, Christine M. Zwart, David H. Frakes, and Baoxin Li "Spatiotemporal video deinterlacing using control grid interpolation," Journal of Electronic Imaging 24(2), 023022 (30 March 2015). https://doi.org/10.1117/1.JEI.24.2.023022
Published: 30 March 2015
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KEYWORDS
Video

Visualization

Digital filtering

Control systems

Image filtering

Motion estimation

Signal to noise ratio

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