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A kind of fast block-matching algorithms which do not introduce any prediction error as compared with the full-search algorithm is to reduce the number of necessary matching evaluations for every searching point in the search window based on partial distortion elimination (PDE), among which winner-update search (WUS) algorithm is a well-known technique. Based on correlation characteristic between gradient magnitudes and matching errors of pixels, this paper proposes an adaptive WUS (AWUS) algorithm which significantly improves the computation efficiency of the original WUS algorithm. This approach can eliminate inappropriate motion vectors faster using an efficient lower bounds set computed according to the edge features of the predicted image. Experimental results indicate that it can accelerate search process by more than 10%, compared with the original WUS algorithm without any loss of estimation accuracy. Furthermore, the proposed algorithm is most suitable for estimating motion vectors for video sequences with rich texture information.