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Proceedings Paper

Optimal block size for block-based motion-compensated video coders
Author(s): Jordi Ribas-Corbera; David L. Neuhoff
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Paper Abstract

In block-based video coding, the current frame to be encoded is decomposed into blocks of the same size, and a motion vector is used to improve the prediction for each block. The motion vectors and the difference frame, which contains the blocks' prediction errors, must be encoded with bits. Typically, choosing a smaller block size will improve the prediction and hence decrease the number of difference frame bits, but it will increase the number of motion bits since more motion vectors need to be encoded. Not surprisingly, there must be some value for the block size that optimizes the tradeoff between motion and difference frame bits, and thus minimizes their sum. Despite the widespread experience with block-based video coders, there is little analysis or theory that quantitatively explains the effect of block size on encoding bit rate, and ordinarily the block size for a coder is chosen based on empirical experiments on video sequences of interest. In this work, we derive a procedure to determine the optimal block size that minimizes the encoding rate for a typical block-based video coder. To do this, we analytically model the effect of block size and derive expressions for the encoding rates for both motion vectors and difference frames, as functions of block size. Minimizing these expressions leads to a simple formula that indicates how to choose the block size in these types of coders. This formula also shows that the best block size is a function of the accuracy with which the motion vectors are encoded and several parameters related to key characteristics of the video scene,such as image texture, motion activity, interframe noise, and coding distortion. We implement the video coder and use our analysis to optimize and explain its performance on real video frames.

Paper Details

Date Published: 10 January 1997
PDF: 12 pages
Proc. SPIE 3024, Visual Communications and Image Processing '97, (10 January 1997); doi: 10.1117/12.263193
Show Author Affiliations
Jordi Ribas-Corbera, Sharp Labs. of America (United States)
David L. Neuhoff, Univ. of Michigan (United States)


Published in SPIE Proceedings Vol. 3024:
Visual Communications and Image Processing '97
Jan Biemond; Edward J. Delp, Editor(s)

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