|
For Full-Text PDF, please login, if you are a member of IEICE,
or go to Pay Per View on menu list, if you are a nonmember of IEICE.
|
A Jointly Optimized Predictive-Adaptive Partitioned Block Transform for Video Coding
Di WU Xiaohai HE
Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Vol.E96-A
No.11
pp.2161-2168 Publication Date: 2013/11/01 Online ISSN: 1745-1337
DOI: 10.1587/transfun.E96.A.2161 Print ISSN: 0916-8508 Type of Manuscript: Special Section PAPER (Special Section on Smart Multimedia & Communication Systems) Category: Image Processing Keyword: even discrete sine transform (EDST), interpolative Markov representation, intra-prediction residuals, blocking artifact,
Full Text: PDF(1.8MB)>>
Summary:
In this paper, we propose a jointly optimized predictive-adaptive partitioned block transform to exploit the spatial characteristics of intra residuals and improve video coding performance. Under the assumptions of traditional Markov representations, the asymmetric discrete sine transform (ADST) can be combined with a discrete cosine transform (DCT) for video coding. In comparison, the interpolative Markov representation has a lower mean-square error for images or regions that have relatively high contrast, and is insensitive to changes in image statistics. Hence, we derive an even discrete sine transform (EDST) from the interpolative Markov model, and use a coding scheme to switch between EDST and DCT, depending on the prediction direction and boundary information. To obtain an implementation independent of multipliers, we also propose an orthogonal 4-point integer EDST, which consists solely of adds and bit-shifts. We implement our hybrid transform coding scheme within the H.264/AVC intra-mode framework. Experimental results show that the proposed scheme significantly outperforms standard DCT and ADST. It also greatly reduces the blocking artifacts typically observed around block edges, because the new transform is more adaptable to the characteristics of intra-prediction residuals.
|
|