An approach to increase the performance of motion estimation algorithms implemented in hardware
WebMedia '06 Proceedings of the 12th Brazilian Symposium on Multimedia and the web
Fast block matching using prediction and rejection criteria
Signal Processing
Journal of Visual Communication and Image Representation
Proposal of an improved motion estimation module for SVC
Proceedings of the 2010 ACM Symposium on Applied Computing
Optimized SAD calculation algorithm for Cell® processor
Companion Proceedings of the XIV Brazilian Symposium on Multimedia and the Web
Configurable complexity-bounded motion estimation for real-time video encoding
ACIVS'05 Proceedings of the 7th international conference on Advanced Concepts for Intelligent Vision Systems
Adaptive search range scaling for b pictures coding
PCM'06 Proceedings of the 7th Pacific Rim conference on Advances in Multimedia Information Processing
Exploration of motion estimation algorithm in graphics processing environment
Proceedings of the 18th Brazilian symposium on Multimedia and the web
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According to the observation on the distribution of motion differentials among the motion vector of any block and those of its four neighboring blocks from six real video sequences, this paper presents a new predictive search area approach for fast block motion estimation. Employing our proposed simple predictive search area approach into the full search (FS) algorithm, our improved FS algorithm leads to 93.83% average execution-time improvement ratio, but only has a small estimation accuracy degradation. We also investigate the advantages of computation and estimation accuracy of our improved FS algorithm when compared to the edge-based search algorithm of Chan and Siu (see IEEE Trans. Image Processing, vol.10, p.1223-1238, Aug. 2001); experimental results reveal that our improved FS algorithm has 74.33% average execution-time improvement ratio and has a higher estimation accuracy. Finally, we further compare the performance among our improved FS algorithm, the three-step search algorithm, and the block-based gradient descent search algorithm.