A Coding and Postprocessing Framework of Multiview Distributed Video for Wireless Video Sensor Networks

In many surveillance application scenarios of wireless video sensor networks (WVSNs), a number of video sensors are deployed, and multidimension monitored the visual information in a region of interest, forming multiview videos. Since the power, computing capability, and bandwidth are very limited in WVSNs, the conventional multiview video coding method is no longer applicable. So multiview distributed video coding (MDVC) emerged and developed rapidly. In this paper, we propose a new multiview video coding and postprocessing framework for multiview videos. First, in coding scheme, motion intense regions (MIRs) and nonmotion intense regions (NMIRs) based on sum of absolute difference (SAD) criteria are distinguished. For the MIR, the side information (SI) is generated by fusion temporal SI and interview spatial SI at the pixel level. But for the NMIR, the temporal SI is directly use as the ultimate SI. Then, to further improve the quality of the decoded image, an image postprocessing scheme is designed by using deblocking and deringing artifact filters on decoded image. Finally, a set of experimental results show that the proposed fusion SI approach can bring improvements up to 0.2-0.5 dB when compares with only temporal SI used. The subsequent decoded videos postprocessing simulation proves that the proposed postprocessing scheme can provide an additional improvement of about 0.1 dB to the decoded video sequences. © 2013 Chong Han et al.