Motion estimation with chessboard pattern prediction strategy

  • Hadi AmirpourEmail author
  • Mohammad Ghanbari
  • Antonio Pinheiro
  • Manuela Pereira


Due to high correlations among the adjacent blocks, several algorithms utilize movement information of spatially and temporally correlated neighbouring blocks to adapt their search patterns to that information. In this paper, this information is used to define a dynamic search pattern. Each frame is divided into two sets, black and white blocks, like a chessboard pattern and a different search pattern is defined for each set. The advantage of this definition is that the number of spatially neighbouring blocks is increased for each current block and it leads to a better prediction for each block. Simulation results show that the proposed algorithm is closer to the Full-Search algorithm in terms of quality metrics such as PSNR than the other state-of-the-art algorithms while at the same time the average number of search points is less.


Video compression Motion estimation Dynamic search pattern Prediction PSNR 



This work is funded by FCT through national funds and co-funded by FEDER-PT2020 partnership agreement under the project PTDC/EEI-PRO/2849/2014 - POCI-01-0145-FEDER-016693, and under the project UID/EEA/50008/2019.


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Authors and Affiliations

  1. 1.Instituto de TelecomunicaçõesUniversidade da Beira InteriorCovilhãPortugal
  2. 2.School of Electrical and Computer Engineering, College of EngineeringUniversity of TehranTehranIran
  3. 3.School of Computer Science and Electronic EngineeringUniversity of EssexColchesterUK

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