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Data embedding in scalable coded video

Authors: LieLin Pang; KokSheik Wong; Sze-Teng Liong;

Data embedding in scalable coded video

Abstract

In this paper, a self-cancelling method is proposed to embed data into multiple layers of a spatial scalable coded video. Correlation of prediction mode from multiple layers are analyzed and exploited to offset the distortion introduced at the base layer(BL) when embedding data at the enhancement layer (EL). Specifically, in the base layer, the prediction modes are divided into two groups, where one group encodes '0' while another encodes '1'. Data embedding in the enhancement layer is designed to compensate the errors introduced in the base layer. Experiment results show that the scalable coded video can effectively carry additional payload in multiple layers while maintaining the video quality and bit rate. In the best case scenario, when 104,141 bits are embedded into the BasketballDrive (BL: 1280 × 720 and EL: 1920 × 1080) video sequence, the bit rate is slightly increased while insignificant degradation in perceptual quality is observed.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
4
Average
Average
Average
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