Journal of Electronic Testing: Theory and Applications
Full-Search-Equivalent Pattern Matching with Incremental Dissimilarity Approximations
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Circuits and Systems for Video Technology
Performance Evaluation of Full Search Equivalent Pattern Matching Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
A fast PDE algorithm using adaptive matching scan order for real-time video coding
ICIAR'10 Proceedings of the 7th international conference on Image Analysis and Recognition - Volume Part I
A High-Performance Low Cost SAD Architecture for Video Coding
IEEE Transactions on Consumer Electronics
Predictive 3D search algorithm for multi-frame motion estimation
IEEE Transactions on Consumer Electronics
New sorting-based partial distortion elimination algorithm for fast optimal motion estimation
IEEE Transactions on Consumer Electronics
A fast exhaustive search algorithm for rate-constrained motion estimation
IEEE Transactions on Image Processing
A new diamond search algorithm for fast block-matching motion estimation
IEEE Transactions on Image Processing
Successive elimination algorithm for motion estimation
IEEE Transactions on Image Processing
A novel unrestricted center-biased diamond search algorithm for block motion estimation
IEEE Transactions on Circuits and Systems for Video Technology
Fast full-search motion estimation based on multilevel successive elimination algorithm
IEEE Transactions on Circuits and Systems for Video Technology
Overview of the Scalable Video Coding Extension of the H.264/AVC Standard
IEEE Transactions on Circuits and Systems for Video Technology
Improvements on Fast Motion Estimation Strategy for H.264/AVC
IEEE Transactions on Circuits and Systems for Video Technology
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Motion estimation (ME) has a variety of applications in image processing, pattern recognition, target tracking, and video compression. In modern video compression standards such as H.264/AVC and HEVC, multiple reference frame ME (MRFME) is adopted to reduce the temporal redundancy between successive frames in a video sequence. In MRFME, the motion search process is conducted using additional reference frames, thereby obtaining better prediction signal as compared to single reference frame ME (SRFME). However, its high computational complexity makes it difficult to be utilized in real-world applications. In order to reduce the computational complexity of MRFME, this paper proposes a level-set-based ME algorithm (LSME) without any penalty in the rate-distortion (RD) performance. First, the proposed algorithm partitions the motion search space into multiple level sets based on a rate constraint. The proposed algorithm then controls the ME process on the basis of the predetermined level sets. Experimental results show that the proposed algorithm reduces the ME time by up to 83.46% as compared to the conventional full search (FS) algorithm.