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Multimedia Tools and Applications

, Volume 78, Issue 14, pp 19603–19619 | Cite as

A Bayer motion estimation for motion-compensated frame interpolation

  • Ran LiEmail author
  • Bingyu Ji
  • Yanling Li
  • Changan Wu
Article
  • 41 Downloads

Abstract

We propose a Bayer ME algorithm which is used to improve the performance of Motion-Compensated Frame Interpolation (MCFI). The core of the proposed algorithm is a predictive model designed from the alternate arrangement of Bayer pattern. According to the predictive model, the Motion Vector Field (MVF) of the interpolated frame is first split into basic blocks and absent blocks, and then an improved Bilateral Motion Estimation (BME) is proposed to compute the MVs of basic blocks. Finally, with the local stationary statistics of MVF, the MV of an absent block is predicted from the MVs of its neighboring basic blocks. Experimental results show that the proposed Bayer ME algorithm can improve both objective and subjective quality of the interpolated frame with a low computational complexity.

Keywords

Motion-compensated frame interpolation Bayer pattern Prediction model Bilateral motion estimation Motion vector prediction 

Notes

Acknowledgements

This work was supported in part by the National Natural Science Foundation of China, under Grants nos. 61501393 and 61572417, in part by Nanhu Scholars Program for Young Scholars of XYNU, and in part by Innovation Team Support Plan of University Science and Technology of Henan Province (No. 19IRTSTHN014).

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Computer and Information TechnologyXinyang Normal UniversityXinyangChina

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