Share Email Print

Proceedings Paper

Fast feature-matching algorithm of motion compensation for hierarchical video CODEC
Author(s): Xiaobing Lee
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

The objective of this investigation is to develop a fast block matching scheme which uses Feature Matching to estimate the Motion Displacement (Motion Vector) of the inter- frame/field blocks in MPEG, ATM, or HDTV video sequences. We study two basic feature models, Sign Truncated Feature (STF) and Maximum Feature (MF) corresponding to the reduced-mean and wavelet hierarchical CODEC structures. The kernel operator is in 2 X 2 pixels and produces a Feature Vector FV (mean, model_pattern). 16 X 16 macro_block of pixels can be iteratively represented as three layered feature vector structures. In the higher resolution layers, the model_pattern alone is sufficient to describe the pixel phase correlations within the block for exclusive matching decisions. Only one or four bits are needed for each 2 X 2 pixel block in the feature vector matching. The reduced data representations make it possible to implement the real-time full range search within a large search window (+/- 32 to +/- 64 pixels). This feature representation can well express the pixel correlations, edges and texture information of the tested blocks. By matching the feature correlations rather than matching the summed pixel-by-pixel intensity values between the current block and the reference block of the previous/future video frame, it is possible to significantly reduce the basis matching complexity by re-using the previous results of feature extraction computations with less data fetching requirements. In addition, half-pixel accuracy motion estimation can be achieved. The propose feature matching algorithm is suitable for pipeline and parallel processing to approach a real time VLSI implementation. It can be more than 10 times faster relative to conventional block matching techniques with the same full range search scheme.

Paper Details

Date Published: 1 November 1992
PDF: 13 pages
Proc. SPIE 1818, Visual Communications and Image Processing '92, (1 November 1992); doi: 10.1117/12.131418
Show Author Affiliations
Xiaobing Lee, Univ. of Toronto (United States)

Published in SPIE Proceedings Vol. 1818:
Visual Communications and Image Processing '92
Petros Maragos, Editor(s)

© SPIE. Terms of Use
Back to Top