A New Fast Block-based Motion Vector Search Algorithm Using Subsampling and Motion Vector Prediction 


Vol. 27,  No. 11, pp. 1065-1073, Nov.  2002


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  Abstract

Recently we need a faster and more accurate motion vector search algorithm in the area of designing an ASIC(Application Specific IC)and a small device. The full search algorithm is computationally intensive even though it can provide the best visual quality. Many algorithms with a reduced number of search locations have been proposed. However. most of these algorithms resulted in a significant loss in estimation accuracy as compared to the full search aglorithm. In this paper, we propose a new fast and efficient search algorithm for block motion estimation that can produce proper visual quality with a significantly reduced computational complexity. The proposed algorithm, NSSP(A New fast block-based Search algorithm using Subsampling and motion vector prediction), is based on the ideas of dithering pattern for pixel decimation and using motion vectors at adjacent macro blacks for prediction. Experimental results show that our approach reduces computational complexity by up to about 50% compared to the well-known conventional fast algorithms while providing comparable visual quality.

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  Cite this article

[IEEE Style]

S. Lee, J. Myung, Y. Cho, S. Oh, C. Ahn, "A New Fast Block-based Motion Vector Search Algorithm Using Subsampling and Motion Vector Prediction," The Journal of Korean Institute of Communications and Information Sciences, vol. 27, no. 11, pp. 1065-1073, 2002. DOI: .

[ACM Style]

Sung-Ho Lee, Jin-Soo Myung, Yong-Gook Cho, Seoung-Jun Oh, and Chang-Beom Ahn. 2002. A New Fast Block-based Motion Vector Search Algorithm Using Subsampling and Motion Vector Prediction. The Journal of Korean Institute of Communications and Information Sciences, 27, 11, (2002), 1065-1073. DOI: .

[KICS Style]

Sung-Ho Lee, Jin-Soo Myung, Yong-Gook Cho, Seoung-Jun Oh, Chang-Beom Ahn, "A New Fast Block-based Motion Vector Search Algorithm Using Subsampling and Motion Vector Prediction," The Journal of Korean Institute of Communications and Information Sciences, vol. 27, no. 11, pp. 1065-1073, 11. 2002.

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pISSN : 1226 - 4717
eISSN : 2287 - 3880