Abstract
Distributed video coding (DVC) is a coding paradigm
that exploits the source statistics at the decoder side
to reduce the complexity at the encoder. The coding efficiency
of DVC critically depends on the quality of side information
generation and accuracy of noise modeling. This paper considers
transform domain Wyner–Ziv (TDWZ) coding and proposes
using optical flow to improve side information generation and
clustering to improve the noise modeling. The optical flow
technique is exploited at the decoder side to compensate for weaknesses
of block-based methods, when using motion-compensation
to generate side information frames. Clustering is introduced
to capture cross band correlation and increase local adaptivity
in the noise modeling. This paper also proposes techniques to
learn from previously decoded WZ frames. Different techniques
are combined by calculating a number of candidate soft side
information for low density parity check accumulate decoding.
The proposed decoder side techniques for side information and
noise learning (SING) are integrated in a TDWZ scheme. On
test sequences, the proposed SING codec robustly improves the
coding efficiency of TDWZ DVC. For WZ frames using a GOP
size of 2, up to 4-dB improvement or an average (Bjøntegaard)
bit-rate savings of 37% is achieved compared with DISCOVER.
that exploits the source statistics at the decoder side
to reduce the complexity at the encoder. The coding efficiency
of DVC critically depends on the quality of side information
generation and accuracy of noise modeling. This paper considers
transform domain Wyner–Ziv (TDWZ) coding and proposes
using optical flow to improve side information generation and
clustering to improve the noise modeling. The optical flow
technique is exploited at the decoder side to compensate for weaknesses
of block-based methods, when using motion-compensation
to generate side information frames. Clustering is introduced
to capture cross band correlation and increase local adaptivity
in the noise modeling. This paper also proposes techniques to
learn from previously decoded WZ frames. Different techniques
are combined by calculating a number of candidate soft side
information for low density parity check accumulate decoding.
The proposed decoder side techniques for side information and
noise learning (SING) are integrated in a TDWZ scheme. On
test sequences, the proposed SING codec robustly improves the
coding efficiency of TDWZ DVC. For WZ frames using a GOP
size of 2, up to 4-dB improvement or an average (Bjøntegaard)
bit-rate savings of 37% is achieved compared with DISCOVER.
| Originalsprog | Engelsk |
|---|---|
| Tidsskrift | I E E E Transactions on Image Processing |
| Vol/bind | 21 |
| Udgave nummer | 12 |
| Sider (fra-til) | 4782-4796 |
| Antal sider | 15 |
| ISSN | 1057-7149 |
| DOI | |
| Status | Udgivet - 2012 |