Please use this identifier to cite or link to this item:
https://scholarhub.balamand.edu.lb/handle/uob/516
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Daba, Jihad S. | en_US |
dc.contributor.author | Priddle, H. | en_US |
dc.date.accessioned | 2020-12-23T08:31:44Z | - |
dc.date.available | 2020-12-23T08:31:44Z | - |
dc.date.issued | 2005 | - |
dc.identifier.uri | https://scholarhub.balamand.edu.lb/handle/uob/516 | - |
dc.description.abstract | Motion estimation forms an important part of video compression systems but is, in general, computationally expensive. There is a growing need for motion estimation algorithms that reduce the processing while yielding good motion estimates, especially for high bit rates sources such as medical video. A common dilemma in video coding is that by speeding up the motion estimation and consequently reducing the processor cost and enabling it to work in real time, the accuracy of the estimate is adversely decreased, causing a reduced compression ratio. A trade-off thus exists between the compression ratio and the processors speed. This paper investigates several novel techniques for achieving good motion estimates at a relatively high speed. The efficiency of these schemes are compared to classical motion estimation techniques in terms of compression capabilities versus processing requirements and are found to be superior to commonly used techniques. | en_US |
dc.format.extent | 5 p. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | IEEE | en_US |
dc.title | Efficient motion estimation schemes for medical video coding | en_US |
dc.type | Conference Paper | en_US |
dc.relation.conference | IEE International Conference on Computational Intelligence in Medicine and Healthcare (CIMED) (2nd : June 2005 : Lisbon, Portugal) | en_US |
dc.contributor.affiliation | Department of Electrical Engineering | en_US |
dc.description.startpage | 418 | en_US |
dc.description.endpage | 423 | en_US |
dc.date.catalogued | 2018-02-05 | - |
dc.description.status | Published | en_US |
dc.identifier.OlibID | 177481 | - |
dc.relation.ispartoftext | Proceedings of the 2nd IEE International Conference on Computational Intelligence in Medicine and Healthcare (CIMED) | en_US |
dc.provenance.recordsource | Olib | en_US |
crisitem.author.parentorg | Faculty of Engineering | - |
Appears in Collections: | Department of Electrical Engineering |
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