Image and Video Compression Standards: Algorithms and Architectures
Image and Video Compression Standards: Algorithms and Architectures
Fast motion estimation within the H.264 codec
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 3 (ICME '03) - Volume 03
A Fast Multi-Resolution Block Matching Algorithm for Multiple-Frame Motion Estimation
IEICE - Transactions on Information and Systems
A fast motion estimation algorithm based on the block sum pyramid
IEEE Transactions on Image Processing
A new diamond search algorithm for fast block-matching motion estimation
IEEE Transactions on Image Processing
Fast block matching algorithm based on the winner-update strategy
IEEE Transactions on Image Processing
A new predictive search area approach for fast block motion estimation
IEEE Transactions on Image Processing
Successive elimination algorithm for motion estimation
IEEE Transactions on Image Processing
A new motion compensation method for image sequence coding using hierarchical grid interpolation
IEEE Transactions on Circuits and Systems for Video Technology
A new three-step search algorithm for block motion estimation
IEEE Transactions on Circuits and Systems for Video Technology
One-dimensional full search motion estimation algorithm for video coding
IEEE Transactions on Circuits and Systems for Video Technology
Pattern Recognition Letters
Block-matching algorithm based on differential evolution for motion estimation
Engineering Applications of Artificial Intelligence
Block matching algorithm for motion estimation based on Artificial Bee Colony (ABC)
Applied Soft Computing
Block-matching algorithm based on harmony search optimization for motion estimation
Applied Intelligence
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In this paper, we present a fast block matching algorithm by making use of the correlation between layers of the sum pyramid for a block. To speed our method, an algorithm is also developed to predict the initial motion vector for a template block. Using the elimination criteria and predicted motion vector, our method can further reduce the computational complexity significantly. Compared with the full search block matching algorithm, our approach can reduce the computing time by a factor of 9.9-28.2 with the peak signal-to-noise ratio (PSNR) degradation of 0.00-0.03dB. Compared to WinUpMI, which is the fastest block matching algorithm preserving global optimality as far as we know, our method can reduce the computing time by 4.9-52.5% with the PSNR degradation of 0.00-0.03dB. Our method can reduce the computing time of predictive search area approach for fast block motion estimation (PSAFBME) by 50-96% with about the same PSNR.