TY - GEN
T1 - Video background modeling under impulse noise
AU - Rodriguez, Paul
AU - Wohlberg, Brendt
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/1/28
Y1 - 2014/1/28
N2 - 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.
AB - 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.
KW - Impulse noise
KW - Principal component pursuit
KW - Video background modeling
UR - http://www.scopus.com/inward/record.url?scp=84949926474&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2014.7025207
DO - 10.1109/ICIP.2014.7025207
M3 - Conference contribution
AN - SCOPUS:84949926474
T3 - 2014 IEEE International Conference on Image Processing, ICIP 2014
SP - 1041
EP - 1045
BT - 2014 IEEE International Conference on Image Processing, ICIP 2014
PB - Institute of Electrical and Electronics Engineers Inc.
ER -