Video background modeling under impulse noise

Abstract

Video background modeling is an important task in many video processing applications. Most existing algorithms assume a Gaussian noise model, but digital videos are, in practice, prone to be degraded by impulse noise, due to transmission errors in wireless or high data-rate wired channels. Principal Component Pursuit (PCP), which also assumes a Gaussian noise model, is currently considered the state of the art for video background modeling. We propose a new PCP-based algorithm that fully integrates the impulse noise model and has computational performance comparable with that of current PCP implementations.

DOI: 10.1109/ICIP.2014.7025207

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@article{Rodriguez2014VideoBM, title={Video background modeling under impulse noise}, author={Paul Rodriguez and Brendt Wohlberg}, journal={2014 IEEE International Conference on Image Processing (ICIP)}, year={2014}, pages={1041-1045} }