Abstract
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power, computing capability, and bandwidth are very limited in WVSNs, the conventional multiview video coding method is no longer applicable.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.
Highlights
Nowadays, with the rapid development of wireless communication and microelectronics technologies, a series of devices and systems relevant with wireless network and video techniques, such as wireless video sensor networks (WVSNs), wireless IP camera, mobile video phone, dense camera arrays, satellite communication systems, and television systems for multiview virtual meeting, have wide application prospects
We study the multiview distributed video coding (MDVC) coding and propose a new MDVC framework, which is constituted by video coding scheme and image postprocessing scheme in WVSNs
When the temporal side information (SI) and spatial SI of a preparing Wyner-Ziv frame have generated, we present a binary masks fusion method to generate SI according the motion intense regions (MIRs) or nonmotion intense regions (NMIRs) type of macroblocks transmitted from encoder
Summary
With the rapid development of wireless communication and microelectronics technologies, a series of devices and systems relevant with wireless network and video techniques, such as wireless video sensor networks (WVSNs), wireless IP camera, mobile video phone, dense camera arrays, satellite communication systems, and television systems for multiview virtual meeting, have wide application prospects These kind of video equipment or systems have a common feature, that is, the computing, data storage, and power consumption capacity are all limited, but all abilities in receiving ends are very powerful. DVC is well suited for camera/video sensor networks, where the correlation across multiple views can be exploited at the decoder, without communications between the cameras/video sensor nodes [8]. This kind of coding scheme for multiview distributed videos is called multiview distributed video coding (MDVC).
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