A Frequency Based Hierarchical Fast Search Block Matching Algorithm for Fast Video Communication

Numerous fast-search block motion estimation algorithms have been developed to circumvent the high computational cost required by the full-search algorithm. These techniques however often converge to a local minimum, which makes them subject to noise and matching errors. Hence, many spatial domain b...

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Veröffentlicht in:International journal of advanced computer science & applications Jg. 7; H. 4
Hauptverfasser: Al-Najdawi, Nijad, Tedmori, Sara, A., Omar, Dorgham, Osama, A., Jafar
Format: Journal Article
Sprache:Englisch
Veröffentlicht: West Yorkshire Science and Information (SAI) Organization Limited 01.01.2016
Schlagworte:
Algorithms
Complexity
Matching
Motion simulation
Search algorithms
Video communication
ISSN:2158-107X, 2156-5570
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Zusammenfassung:Numerous fast-search block motion estimation algorithms have been developed to circumvent the high computational cost required by the full-search algorithm. These techniques however often converge to a local minimum, which makes them subject to noise and matching errors. Hence, many spatial domain block matching algorithms have been developed in literature. These algorithms exploit the high correlation that exists between pixels inside each frame block. However, with the block transformed frequencies, block matching can be used to test the similarities between a subset of selected frequencies that correctly identify each block uniquely; therefore fewer comparisons are performed resulting in a considerable reduction in complexity. In this work, a two-level hierarchical fast search motion estimation algorithm is proposed in the frequency domain. This algorithm incorporates a novel search pattern at the top level of the hierarchy. The proposed hierarchical method for motion estimation not only produces consistent motion vectors within each large object, but also accurately estimates the motion of small objects with a substantial reduction in complexity when compared to other benchmark algorithms.
Bibliographie:ObjectType-Article-1
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ISSN:2158-107X
2156-5570
DOI:10.14569/IJACSA.2016.070459