標題: Fast full search in motion estimation by hierarchical use of Minkowski's inequality (humi)
作者: Lu, JY
Wu, KS
Lin, JC
資訊工程學系
Department of Computer Science
關鍵字: motion estimation;block matching;position vector;motion vector;accumulated absolute distortion;Minkowski's inequality;l(1)-norm
公開日期: 1-Jul-1998
摘要: In this paper, we extend the idea of successive elimination algorithm (SEA) to obtain a fast full search (FS) algorithm accelerating the block matching procedure of motion estimation. Based on the monotonic relation between the accumulated absolution distortions (AAD) obtained for distinct layers of a pyramid structure; the proposed method successfully rejects many impossible candidates considered in the FS. The derivation of the monotonicity relation repeatedly uses in a four-dimensional vector space the l(1)-version of Minkowski's inequality, an inequality which is quite well-known in the field of mathematics. Simulation results show that the processing speed is faster than that of several well-known fast full search methods, including the SEA that uses just once the Minkowski's inequality (in a vector space of 256 dimension when the block size is 16 x 16). The processing speed of the proposed method is also competitive with that of the three-step search (TSS), which is often used for block matching in interframe video coding, although the visual quality performance of TSS is usually a little poorer than that of the FS. (C) 1998 Pattern Recognition Society. Published by Elsevier Science Ltd. All rights reserved.
URI: http://hdl.handle.net/11536/32532
ISSN: 0031-3203
期刊: PATTERN RECOGNITION
Volume: 31
Issue: 7
起始頁: 945
結束頁: 952
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