Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/12182
Title: New weighted prediction architecture for coding scenes with various fading effects image and video processing
Authors: Tsang, SH
Chan, YL 
Siu, WC 
Keywords: Brightness variations
H.264
Multiple reference frames
Weighted prediction
Issue Date: 2010
Source: SIGMAP 2010 - Proceedings of the International Conference on Signal Processing and Multimedia Applications, 2010, p. 118-123 How to cite?
Abstract: Weighted prediction (WP) is one of the new tools in H.264 for encoding scenes with brightness variations. However, a single WP model does not handle all types of brightness variations. Also, large luminance difference induced by object motions would mislead an encoder in its use of WP which results in low coding efficiency. To solve these problems, a picture-based multi-pass encoding strategy, which extensively encodes the same picture multiple times with different WP models and selects the model with the minimum rate-distortion cost, has been adopted in H.264 to obtain better coding performance. However, computational complexity is unpractically high. In this paper, a new WP referencing architecture is proposed to facilitate the use of multiple WP models by making a new arrangement of multiple frame buffers in multiple reference frame motion estimation. Experimental results show that the proposed scheme can improve prediction in scenes with different types of brightness variations and considerable luminance difference induced by motions within the same sequence.
Description: International Conference on Signal Processing and Multimedia Applications, SIGMAP 2010, Athens, 26-28 July 2010
URI: http://hdl.handle.net/10397/12182
ISBN: 9789898425195
Appears in Collections:Conference Paper

Access
View full-text via PolyU eLinks SFX Query
Show full item record

SCOPUSTM   
Citations

2
Last Week
1
Last month
Citations as of Sep 17, 2017

Page view(s)

47
Last Week
0
Last month
Checked on Sep 24, 2017

Google ScholarTM

Check



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.