Distributed video coding is a relatively new video coding ap-
proach, where compression is achieved by performing motion estimation
at the decoder. Current techniques for decoder-side motion estimation
make use of assumptions such as linear motion between the reference
frames. It is only after the frame is partially decoded that some of the
errors are corrected. In this paper, we propose a new approach with mul-
tiple predictors, accounting for inaccuracies in the decoder-side motion
estimation process during the decoding. Each of the predictors is assigned
a weight, and the correlation between the original frame at the encoder
and the set of predictors at the decoder is modeled at the decoder. This
correlation information is then used during the decoding process. Results
indicate average quality gains up to 0.4 dB.
Slowack, J, Skorupa, J, Mys, S , Deligiannis, N , Lambert, P , Munteanu, A & Van De Walle, R 2010, Compensating for motion estimation inaccuracies in distributed video coding . in Image & S Processing (eds), Lecture Notes in Computer Science. Springer Verlag, pp. 324-332.
Slowack, J., Skorupa, J., Mys, S. , Deligiannis, N. , Lambert, P. , Munteanu, A. , & Van De Walle, R. (2010). Compensating for motion estimation inaccuracies in distributed video coding . In Image, & S. Processing (Eds.), Lecture Notes in Computer Science (pp. 324-332). Springer Verlag.
@inbook{3487cfd16f484a5da454e7b69166574f,
title = " Compensating for motion estimation inaccuracies in distributed video coding " ,
abstract = " Distributed video coding is a relatively new video coding ap- proach, where compression is achieved by performing motion estimation at the decoder. Current techniques for decoder-side motion estimation make use of assumptions such as linear motion between the reference frames. It is only after the frame is partially decoded that some of the errors are corrected. In this paper, we propose a new approach with mul- tiple predictors, accounting for inaccuracies in the decoder-side motion estimation process during the decoding. Each of the predictors is assigned a weight, and the correlation between the original frame at the encoder and the set of predictors at the decoder is modeled at the decoder. This correlation information is then used during the decoding process. Results indicate average quality gains up to 0.4 dB. " ,
keywords = " distributed video coding " ,
author = " Jurgen Slowack and Jozef Skorupa and Stefaan Mys and Nikolaos Deligiannis and Peter Lambert and Adrian Munteanu and {Van De Walle}, Rik " ,
note = " Image and Signal Processing " ,
year = " 2010 " ,
month = aug,
language = " English " ,
isbn = " 978-3-642-13680-1 " ,
pages = " 324332 " ,
editor = " Image and Signal Processing " ,
booktitle = " Lecture Notes in Computer Science " ,
publisher = " Springer Verlag " ,
address = " Germany " ,
}