Enhanced Cross Search algorithm using Predicted Motion vector for Fast Block Motion Estimation
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Ko, Byung-Kwan | - |
dc.contributor.author | Tong III, Kwak | - |
dc.contributor.author | Hwang, Bo-Hyun | - |
dc.contributor.author | Yun, Jong-Ho | - |
dc.contributor.author | Choi, Myung-Ryul | - |
dc.date.accessioned | 2021-06-23T17:04:05Z | - |
dc.date.available | 2021-06-23T17:04:05Z | - |
dc.date.issued | 2008-10 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/42110 | - |
dc.description.abstract | Various Motion Estimation (ME) algorithms have been proposed since ME requires large computational complexity. The proposed algorithm employs Enhanced Cross Search Pattern (ECSP) using motion vector of neighbor-blocks to search the motion vector. The experimental results show that proposed algorithm reduces the search point up to 35% compared to conventional methods. | - |
dc.format.extent | 4 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | KIDS , SID , USDC , DisplaySearch | - |
dc.title | Enhanced Cross Search algorithm using Predicted Motion vector for Fast Block Motion Estimation | - |
dc.type | Article | - |
dc.identifier.scopusid | 2-s2.0-65649116181 | - |
dc.identifier.bibliographicCitation | IMID (International Meeting on Information Display) 2008, pp 749 - 752 | - |
dc.citation.title | IMID (International Meeting on Information Display) 2008 | - |
dc.citation.startPage | 749 | - |
dc.citation.endPage | 752 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | other | - |
dc.subject.keywordAuthor | Motion estimation | - |
dc.subject.keywordAuthor | Motion vector | - |
dc.subject.keywordAuthor | Sum of absolute difference | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
55 Hanyangdeahak-ro, Sangnok-gu, Ansan, Gyeonggi-do, 15588, Korea+82-31-400-4269 sweetbrain@hanyang.ac.kr
COPYRIGHT © 2021 HANYANG UNIVERSITY. ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.