Paper
1 October 1998 Modified block-matching motion estimation algorithm for object-based video coding
Mei-Juan Chen, Pei-Chun Lee, Po-Yuen Cheng
Author Affiliations +
Abstract
Block-matching motion estimation algorithms (BMAs) are widely used to eliminate temporal redundancies for video coding. For BMAs, there is an implicit assumption that the motion within each block is uniform. It is not always valid if the fixed block size is not approximate to the real object in an image. Then the block effect will be noticeable and the quality of the prediction suffers. In this paper, the block-classified motion estimation algorithm is presented. The proposed algorithm classifies the frame into stationary and moving object blocks. The object blocks are then adaptively segmented into different regions according to their motion and edge characteristics. The proposed method can estimate the edge blocks accurately. Experimental results show that this scheme has better performance in terms of objective and subjective measures than the full search and variable block-size quadtree segmentation motion estimation algorithms.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mei-Juan Chen, Pei-Chun Lee, and Po-Yuen Cheng "Modified block-matching motion estimation algorithm for object-based video coding", Proc. SPIE 3460, Applications of Digital Image Processing XXI, (1 October 1998); https://doi.org/10.1117/12.323202
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KEYWORDS
Motion estimation

Image segmentation

Image processing algorithms and systems

Video coding

Algorithm development

Binary data

Terbium

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