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A neighbourhood analysis based technique for real-time error concealment in H.264 intra pictures

Beesley, Steven T. C., Grecos, Christos and Edirisinghe, Eran (2007) A neighbourhood analysis based technique for real-time error concealment in H.264 intra pictures. Proceedings of SPIE - The International Society for Optical Engineering, 6507. p. 650706. ISSN 0277-786X

Full text not available from this repository.
Official URL: http://dx.doi.org/10.1117/12.704866

Abstract

H.264s extensive use of context-based adaptive binary arithmetic or variable length coding makes streams highly susceptible to channel errors, a common occurrence over networks such as those used by mobile devices. Even a single bit error will cause a decoder to discard all stream data up to the next fixed length resynchronisation point, the worst scenario is that an entire slice is lost. In cases where retransmission and forward error concealment are not possible, a decoder should conceal any erroneous data in order to minimise the impact on the viewer. Stream errors can often be spotted early in the decode cycle of a macroblock which if aborted can provide unused processor cycles, these can instead be used to conceal errors at minimal cost, even as part of a real time system. This paper demonstrates a technique that utilises Sobel convolution kernels to quickly analyse the neighbourhood surrounding erroneous macroblocks before performing a weighted multi-directional interpolation. This generates significantly improved statistical (PSNR) and visual (IEEE structural similarity) results when compared to the commonly used weighted pixel value averaging. Furthermore it is also computationally scalable, both during analysis and concealment, achieving maximum performance from the spare processing power available.

Item Type: Article
Subjects: Q Science > QA Mathematics > Electronic computers. Computer science
T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science
Z Bibliography. Library Science. Information Resources > ZA Information resources > ZA4150 Computer Network Resources
Divisions: School of Computing > Staff Research and Publications
Depositing User: Caoimhe Ní Mhaicín
Date Deposited: 07 Mar 2019 13:53
Last Modified: 07 Mar 2019 13:53
URI: https://norma.ncirl.ie/id/eprint/3711

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