Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Survey on Block Matching Motion Estimation Algorithms and Architectures with New Results
Journal of VLSI Signal Processing Systems
A fast feature-based block matching algorithm using integral projections
IEEE Journal on Selected Areas in Communications
A new diamond search algorithm for fast block-matching motion estimation
IEEE Transactions on Image Processing
New adaptive pixel decimation for block motion vector estimation
IEEE Transactions on Circuits and Systems for Video Technology
Efficient block motion estimation using integral projections
IEEE Transactions on Circuits and Systems for Video Technology
Fast motion vector estimation using multiresolution-spatio-temporal correlations
IEEE Transactions on Circuits and Systems for Video Technology
A globally adaptive pixel-decimation algorithm for block-motion estimation
IEEE Transactions on Circuits and Systems for Video Technology
Probabilistic partial-distance fast matching algorithms for motion estimation
IEEE Transactions on Circuits and Systems for Video Technology
Fast full-search block matching
IEEE Transactions on Circuits and Systems for Video Technology
A novel all-binary motion estimation (ABME) with optimized hardware architectures
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
A hierarchical N-Queen decimation lattice and hardware architecture for motion estimation
IEEE Transactions on Circuits and Systems for Video Technology
New fast algorithms for the estimation of block motion vectors
IEEE Transactions on Circuits and Systems for Video Technology
A new block-matching criterion for motion estimation and its implementation
IEEE Transactions on Circuits and Systems for Video Technology
A neighborhood elimination approach for block matching in motion estimation
Image Communication
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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This paper presents a boundary-based approach towards pixel decimation with applications in block-matching algorithms (BMAs). The proposed approach is based on the observation that new objects usually enter macroblocks (MBs) through their boundaries. The MBs are selected based on boundary region matching only. The boundary-based patterns can be used to speed up motion estimation with marginal loss in image quality. Different decimation levels for image quality trade-off with computational power have been presented. The mathematical intuition in support of the proposed patterns has been discussed. Apart from the boundary-based approach, the novelty in our contribution also lies in performing a genetic algorithm (GA)-based search to find optimal M-length patterns in an NxN block. The resultant patterns are found to have better values of spatial homogeneity and directional coverage metrics, as compared to the recently proposed N-queen decimation lattices. Subsequently, we obtain new pixel-decimation patterns by combining the proposed boundary-based patterns with N-queen patterns and the GA-based patterns. Experimental results demonstrate considerably improved coding efficiency and comparable prediction quality of these new patterns as compared to existing decimation lattices.