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Proceedings 2017, 1(3), 134; doi:10.3390/IS4SI-2017-04002

Error Resilient Video Coding for Wireless Visual Sensor Network

College of Electronics and Information Engineering, Sichuan University, No. 24 South Section 1, Yihuan Road, Chengdu 610065, China
Chengdu College of University of Electronic Science and Technology of China, No. 4, Section 2, Construction North Road, Chengdu 611731, China
Faculty of Computer Science, University of Sunderland, St Peter Campus, Sunderland SR6 0DD, UK
Presented at the IS4SI 2017 Summit DIGITALISATION FOR A SUSTAINABLE SOCIETY, Gothenburg, Sweden, 12–16 June 2017.
Author to whom correspondence should be addressed.
Published: 9 June 2017
(This article belongs to the Proceedings of the IS4SI 2017 Summit DIGITALISATION FOR A SUSTAINABLE SOCIETY)
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This work proposes an error-resilient video coding scheme for improving the ecosystem of Wireless Visual Sensor Network (WVSN). In order to optimize the video information communication over WVSN, this work first provides a discussion on ecology technology model of video transmission in the WVSNs. And then proposes a Distributed Video Parallel Coding scheme, which make use of the correlation of video information in the decoder side, to cope with the loss of video data over wireless error-prone channel. Specifically, this work proposes a Partition Irregular Repeat Accumulate codec, which exhibits better error resilience performance and obtain the same compression ratio with traditional video coding method. The experimental results indicate that the performance of the proposed Distributed Video Parallel Coding scheme is promising and can better optimize the ecosystem of video communication over WVSN.
Keywords: Wireless Visual Sensor Network; Error Resilient; Distributed Video Coding Wireless Visual Sensor Network; Error Resilient; Distributed Video Coding
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Yang, H.; Qing, L.; Peng, Y.; He, X. Error Resilient Video Coding for Wireless Visual Sensor Network. Proceedings 2017, 1, 134.

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