An adaptive search algorithm based on block classification for fast block motion estimation

  • Meng Chou Chang*
  • , Jung Shan Chien
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

This paper presents a new motion estimation algorithm, called the adaptive motion estimation (AME). The AME algorithm exploits the information gathered from the previous frame to derive a parameter, called CF (Correlation Parameter), and employs CF to classify the blocks in the current frame into potentially dependent blocks and potentially independent blocks. AME applies different motion estimation methods for potentially dependent blocks and potentially independent blocks to achieve better estimation accuracy and lower computational complexity. Simulation results showed that the proposed AME algorithm has both lower computational complexity and higher PSNR than other motion estimation algorithms, such as three-step search (TSS), new three-step search (NTSS), four-step search (4SS), and the NPSA (new predictive search area) algorithm.

Original languageEnglish
Title of host publicationISCAS 2006
Subtitle of host publication2006 IEEE International Symposium on Circuits and Systems, Proceedings
Pages3982-3985
Number of pages4
StatePublished - 2006
Externally publishedYes
EventISCAS 2006: 2006 IEEE International Symposium on Circuits and Systems - Kos, Greece
Duration: 21 05 200624 05 2006

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
ISSN (Print)0271-4310

Conference

ConferenceISCAS 2006: 2006 IEEE International Symposium on Circuits and Systems
Country/TerritoryGreece
CityKos
Period21/05/0624/05/06

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