A Spatial Prediction-Based Motion-Compensated Frame Rate Up-Conversion

Yanli Li, Wendan Ma and Yue Han
Additional contact information
Yanli Li: School of Computer and Information Technology, Xinyang Normal University, Xinyang 464000, China
Wendan Ma: School of Computer and Information Technology, Xinyang Normal University, Xinyang 464000, China
Yue Han: School of Computer and Information Technology, Xinyang Normal University, Xinyang 464000, China

Future Internet, 2019, vol. 11, issue 2, 1-10

Abstract: In Multimedia Internet of Things (IoT), in order to reduce the bandwidth consumption of wireless channels, Motion-Compensated Frame Rate Up-Conversion (MC-FRUC) is often used to support the low-bitrate video communication. In this paper, we propose a spatial predictive algorithm which is used to improve the performance of MC-FRUC. The core of the proposed algorithm is a predictive model to split a frame into two kinds of blocks: basic blocks and absent blocks. Then an improved bilateral motion estimation is proposed to compute the Motion Vectors (MVs) of basic blocks. Finally, with the spatial correlation of Motion Vector Field (MVF), the MV of an absent block is predicted based on the MVs of its neighboring basic blocks. Experimental results show that the proposed spatial prediction algorithm can improve both the objective and the subjective quality of the interpolated frame, with a low computational complexity.

Keywords: motion-compensated frame interpolation; spatial correlation; bilateral motion estimation; successive elimination algorithm (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2019
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1999-5903/11/2/26/pdf (application/pdf)
https://www.mdpi.com/1999-5903/11/2/26/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jftint:v:11:y:2019:i:2:p:26-:d:200332

Access Statistics for this article

Future Internet is currently edited by Ms. Grace You

More articles in Future Internet from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().