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Fast Motion Estimation Algorithm using Filters of Multiple Thresholds  

Kim, Jong-Nam (Dept. of IT Convergence & Applications Engineering, Pukyong National University)
Publication Information
Journal of the Institute of Convergence Signal Processing / v.19, no.4, 2018 , pp. 199-205 More about this Journal
Abstract
So many fast motion estimation algorithms for prediction quality and computational reduction have been published due to tremendous computations of full search algorithm. In the paper, we suggest an algorithm that reduces computation effectively, while keeping prediction quality as almost same as that of the full search. The proposed algorithm based on multiple threshold filter calculates the sum of partial block matching error for each candidate, selects the candidates for the next step, compares the stability of optimal candidates with minimum error, removes impossible candidates, and calculates optimal motion vectors by determining the progress of the next step. By doing that, we can find the minimum error point as soon as possible and obtain the better performance of calculation speed by reducing unnecessary computations. The proposed algorithm can be combined with conventional fast motion estimation algorithms as well as by itself, further reduce computation while keeping the prediction quality as almost same as the algorithms, and prove it in the experimental results.
Keywords
Motion estimation; Optimal candidate; Video coding; Block matching; Partial block error;
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