Video background modeling under impulse noise

Paul Rodriguez, Brendt Wohlberg

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9 Citas (Scopus)


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.

Idioma originalInglés
Título de la publicación alojada2014 IEEE International Conference on Image Processing, ICIP 2014
EditorialInstitute of Electrical and Electronics Engineers Inc.
Número de páginas5
ISBN (versión digital)9781479957514
EstadoPublicada - 28 ene. 2014

Serie de la publicación

Nombre2014 IEEE International Conference on Image Processing, ICIP 2014


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