Improved Side Information Generation for Distributed Video Coding by Exploiting Spatial and Temporal Correlations

Abstract

Distributed video coding (DVC) is a video coding paradigm allowing low complexity encoding for emerging applications such as wireless video surveillance. Side information (SI) generation is a key function in the DVC decoder, and plays a key-role in determining the performance of the codec. This paper proposes an improved SI generation for DVC, which exploits both spatial and temporal correlations in the sequences. Partially decoded Wyner-Ziv (WZ) frames, based on initial SI by motion compensated temporal interpolation, are exploited to improve the performance of the whole SI generation. More specifically, an enhanced temporal frame interpolation is proposed, including motion vector refinement and smoothing, optimal compensation mode selection, and a new matching criterion for motion estimation. The improved SI technique is also applied to a new hybrid spatial and temporal error concealment scheme to conceal errors in WZ frames. Simulation results show that the proposed scheme can achieve up to 1.0 dB improvement in rate distortion performance in WZ frames for video with high motion, when compared to state-of-the-art DVC. In addition, both the objective and perceptual qualities of the corrupted sequences are significantly improved by the proposed hybrid error concealment scheme, outperforming both spatial and temporal concealments alone.

Improving distributed video coding side information by intelligently combining macro-blocks from multiple algorithms

“…This is achieved by minimizing SBAD [10], which measures the spatial error of the MB under consideration between the reference and current HOPTTI frames. Since the original current frame is not available at the decoder, the previous key frame is used as the reference frame [7]. …”

“…SIs are the coarse representation of these WZ frames, which are not available at the decoder. Hence the quality of SI has a major impact on the resulting DVC output quality [4][5][6][7]. SI is commonly generated using linear-motion compensated temporal interpolation (LMCTI) [3][4][5] and while this generally provides reasonable quality, it does not always afford an adequate formulation as motion in real sequences is not always linear.…”

Correlation Noise Estimation in Distributed Video Coding

“…Information about the (partially) decoded frame can also be used to re-evaluate the side information generation process, for example, by identifying "suspicious" (i.e. possibly wrong) motion vectors (Ye et al (2009)). While these techniques show good results, what they have in common is that they can compensate for mistakes only after some information has been decoded.…”

Efficient hash-driven Wyner-Ziv video coding for visual sensors

“…However, MCI assumes a linear motion model which falls short in case of irregular motion [10]. To alleviate this problem, joint decoding and sideinformation refinement [12], [13], [14], [15], or hash-based motion estimation [16], [17], [18], [19] have been proposed.…”