Fast motion estimation based on search range adjustment and matching point decimation

نویسنده

  • S. Lee
چکیده

This study introduces a new fast motion estimation (ME) based on both an adaptive search range adjustment and a matching point decimation. In particular, the authors present a maximum matching error constraint in the matching phase that can eliminate an impossible candidate block much earlier than a conventional partial distortion elimination (PDE) scheme. The constraint is computed during the matching error computation based on sum of absolute difference (SAD) between two blocks. The basic idea of the proposed scheme is based on adjusting a given search range adaptively and early eliminating invalid matching blocks effectively. The adaptive search range adjustment is first performed by analysing the contents of a scene. Next, a maximum partial matching error in reordered sub-blocks of an optimal block is obtained, and it is set as a trigger to eliminate invalid blocks for ME. The main contributions of the proposed scheme are that (i) it can reduce a search range adaptively based on the analysis of scene contents; (ii) it can make an early decision for an impossible candidate before complete SAD computation; (iii) the proposed constraint can reduce the computational cost considerably for SAD calculation; and (iv) the proposed matching ideas can be applied to conventional PDE algorithms without significant changes. In order to evaluate the proposed scheme, several baseline approaches are described and compared. The experimental results show that the proposed algorithm can reduce the computational cost more than 86% for ME at the cost of 0.02 dB quality degradation on against the conventional PDE algorithm.

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تاریخ انتشار 2009