NDLI: Adaptively weighted update steps using chrominance for scalable video coding

Content Provider	IEEE Xplore Digital Library
Author	Fengling Li Nam Ling
Copyright Year	2005
Description	Author affiliation: Dept. of Comput. Eng., Santa Clara Univ., CA, USA (Fengling Li; Nam Ling)
Abstract	Scalable video coding using motion-compensated temporal filtering is one of the latest trends in video coding standardization. In the lifting based motion-compensated temporal filtering framework, such as that in the joint scalable video model (JSVM), the data used in the update steps are basically the residuals from the motion-compensated prediction. When the motion model used in the prediction steps fails to capture the true motion, energy in the high-pass temporal frames becomes substantial and strong ghosting artifacts may be introduced to the low-pass frames during the update steps. In this paper we propose a new block-based update approach, which takes advantage of the chrominance information of the video sequence to further reduce ghosting artifacts in low-pass temporal frames. We adaptively weight the update steps according to the energy not only of luminance pixels, but also of chrominance pixels in the high-pass temporal frames at the corresponding locations. Experimental results show that the proposed algorithm can significantly improve the quality of the reconstructed video sequence, in PSNR and visual quality.
Starting Page	682
Ending Page	687
File Size	411555
Page Count	6
File Format	PDF
ISBN	0780393333
ISSN	15206130
DOI	10.1109/SIPS.2005.1579952
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-11-02
Publisher Place	Greece
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Video coding Filtering Predictive models Filter bank Motion estimation Video sequences PSNR Scalability Humans Machine vision
Content Type	Text
Resource Type	Article

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