Wyner-Ziv video coding has been widely investigated in recent years. The main characteristic of Wyner-Ziv
coding is that side information is available only to the decoder. Many current Wyner-Ziv video coding schemes
encode the sequences using two approaches which separate the frames into what are known as key frames and
Wyner-Ziv frames. Key frames are encoded using conventional video coding methods and Wyner-Ziv frames
are encoded using channel coding techniques. At the decoder, the reconstructed key frames serve as the side
information used to reconstruct the Wyner-Ziv frames. We have previously presented a Wyner-Ziv scheme
that uses backward-channel-aware motion estimation to encode the key frames, where motion estimation was
performed at the decoder and motion information was transmitted back to the encoder. We refer to these
backward predictively coded frames as BP frames. In this paper, we extend our previous work to describe three
types of motion estimators. We present a model to examine the analytical complexity-rate-distortion performance
of BP frames for the three motion estimators.
Motion estimation is the most important step in the video compression. Most of the current video compression
systems use forward motion estimation, where motion information is derived at the encoder and sent to the
decoder over the channel. Backward motion estimation does not derive an explicit representation of motion
at the encoder. Instead, the encoder implicitly embeds the motion information in an alternative subspace.
Most recently, an algorithm that adopts least-square prediction (LSP) for backward motion estimation has
shown great potential to further improve coding efficiency. Forward motion estimation and backward motion
estimation have both their advantages and disadvantages. Each is suitable for handling some specific category of
patterns. In this paper, we propose a novel approach that combines both forward motion estimation and backward
motion estimation in one framework to adaptively exploit the local motion characteristics in an arbitrary video
sequence, thus achieving better coding efficiency. We refer to this as Content-Adaptive Motion Estimation
(CoME). The encoder in the proposed system is able to adjust the motion estimation method in a rate-distortion
optimized manner. According to the experimental results, CoME reduces the data rate in both lossless and lossy
The coding efficiency of a Wyner-Ziv video codec relies significantly on the quality of side information extracted at the decoder. The construction of efficient side information is difficult thanks in part to the fact that the original video sequence is not available at the decoder. Conventional motion search methods are widely used in the Wyner-Ziv video decoder to extract side information. This substantially increases the Wyner-Ziv video decoding complexity. In this paper, we propose a new method to construct side estimation based on the idea of universal prediction. This method, referred to as Wyner-Ziv video coding with Universal Prediction(WZUP), does not perform motion search or assume underlying model of original input video sequences at the decoder. Instead, WZUP estimates the side
information based on its observations on past reconstructed video
data. We show that WZUP can significantly reduce decoding complexity at the decoder and achieve fair side estimation performance, thus make it possible to design both the video encoder and the decoder with low computational complexity.
Previously we presented a network-driven Wyner-Ziv video coding method, in which the motion vectors are derived at the decoder and sent back to the encoder through a reliable backward channel. In this paper, we consider the scenario when the backward channel is error resilient. We study the performance of error resilient methods for our codec. A symmetrical Reversible Variable Length Code (RVLC) is used to reduce the bandwidth requirement of the backward channel. A hybrid scheme with selective coding is proposed to improve the coding
efficiency when transmission delay occurs. The experimental results show that these error resilient methods can consistently improve the video quality at the decoder.
Wyner-Ziv video coding has gained considerable interests in the research community. In this paper, we examine the Wyner-Ziv video coding performance and compare it with conventional motion-compensated prediction (MCP) based video coding. Theoretical and simulation results show that although Wyner-Ziv video coding can
achieve as much as 6dB gain over conventional video coding without motion search, it still falls 6dB or more behind current best MCP-based INTER-frame video coding. We further investigate the use of sub-pixel and multi-reference motion search methods to improve Wyner-Ziv video coding efficiency.
In some video applications such as video surveillance, a simple encoder is preferred and the computational intensive jobs shall be left to the decoder. It is pointed out in Wyner and Ziv’s paper that this goal is achievable by exploiting video source statistics only at the decoder. In many existing Wyner-Ziv video coding schemes, a lot of frames have to be intra coded so that the decoder can derive sufficiently accurate side information from the I frames. In this paper we present a new network-drive Wyner-Ziv method using forward prediction. The basic idea is to perform motion estimation at the decoder and send motion information back to the encoder through the feedback channel. We implement our approach by modifying the H.264 video codec JM8.0 with different configurations. The results show that our proposed approach can improve coding efficiency compared to other Wyner-Ziv video coding schemes.