In the context of low-cost video encoding, distributed video coding (DVC) has recently emerged as a potential candidate for uplink-oriented applications. This paper builds on a correlation channel modeling concept which expresses the correlation noise as being statistically dependent on the side-information. Compared to classical side-information independent noise model-ing adopted in current DVC solutions, it is theoretically proven that side-information dependent modeling improves the Wyner-Ziv coding performance. Anchored in this finding, this paper proposes a novel algorithm for online estimation of the side-information dependent correlation channel parameters based on already decoded information. The proposed algorithm enables bit-plane-by-bit-plane successive refinement of the channel esti-mation leading to progressively improved accuracy. Additionally, the proposed algorithm is included in a novel DVC architecture which employs a competitive hash-based motion estimation tech-nique to generate high quality side-information at the decoder. Experimental results corroborate our theoretical gains and vali-date the accuracy of the channel estimation algorithm. The per-formance assessment of the proposed architecture shows remark-able and consistent coding gains over a germane group of state-of-the-art distributed and standard video codecs, even under strenuous conditions, that is, large groups of pictures (GOP) and highly irregular motion content.
Deligiannis, N, Barbarien, J, Jacobs, M, Munteanu, A, Skodras, A & Schelkens, P 2012, 'Side-information dependent correlation channel estimation in hash-based distributed video coding', IEEE Transactions on Image Processing, vol. 21, no. April 2012, pp. 1934-1949. <http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=6111476&url=http%3A%2F%2Fieeexplore.ieee.org%2Fiel5%2F83%2F4358840%2F06111476.pdf%3Farnumber%3D6111476>
Deligiannis, N., Barbarien, J., Jacobs, M., Munteanu, A., Skodras, A., & Schelkens, P. (2012). Side-information dependent correlation channel estimation in hash-based distributed video coding. IEEE Transactions on Image Processing, 21(April 2012), 1934-1949. http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=6111476&url=http%3A%2F%2Fieeexplore.ieee.org%2Fiel5%2F83%2F4358840%2F06111476.pdf%3Farnumber%3D6111476
@article{0b33f7fdf71848cfb2868c50e238299e,
title = "Side-information dependent correlation channel estimation in hash-based distributed video coding",
abstract = "In the context of low-cost video encoding, distributed video coding (DVC) has recently emerged as a potential candidate for uplink-oriented applications. This paper builds on a correlation channel modeling concept which expresses the correlation noise as being statistically dependent on the side-information. Compared to classical side-information independent noise model-ing adopted in current DVC solutions, it is theoretically proven that side-information dependent modeling improves the Wyner-Ziv coding performance. Anchored in this finding, this paper proposes a novel algorithm for online estimation of the side-information dependent correlation channel parameters based on already decoded information. The proposed algorithm enables bit-plane-by-bit-plane successive refinement of the channel esti-mation leading to progressively improved accuracy. Additionally, the proposed algorithm is included in a novel DVC architecture which employs a competitive hash-based motion estimation tech-nique to generate high quality side-information at the decoder. Experimental results corroborate our theoretical gains and vali-date the accuracy of the channel estimation algorithm. The per-formance assessment of the proposed architecture shows remark-able and consistent coding gains over a germane group of state-of-the-art distributed and standard video codecs, even under strenuous conditions, that is, large groups of pictures (GOP) and highly irregular motion content.",
keywords = "distributed video coding, hash information, overlapped block motion estimation, correlation channel, online successively refined channel estimation, video coding",
author = "Nikolaos Deligiannis and Joeri Barbarien and Marc Jacobs and Adrian Munteanu and Athanassios Skodras and Peter Schelkens",
year = "2012",
month = apr,
language = "English",
volume = "21",
pages = "1934--1949",
journal = "IEEE Transactions on Image Processing",
issn = "1057-7149",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
number = "April 2012",
}