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

1,2,*, 1,2 and 1,2
1
School of Computer and Information Technology, Xinyang Normal University, Xinyang 464000, China
2
Henan Key Lab of Analysis and Applications of Education Big Data, Xinyang Normal University, Xinyang 464000, China
*
Author to whom correspondence should be addressed.
Future Internet 2019, 11(2), 26; https://doi.org/10.3390/fi11020026
Received: 30 December 2018 / Revised: 13 January 2019 / Accepted: 21 January 2019 / Published: 23 January 2019
(This article belongs to the Special Issue Multimedia Internet of Things (IoT) in Smart Environment)
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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. View Full-Text
Keywords: motion-compensated frame interpolation; spatial correlation; bilateral motion estimation; successive elimination algorithm motion-compensated frame interpolation; spatial correlation; bilateral motion estimation; successive elimination algorithm
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Li, Y.; Ma, W.; Han, Y. A Spatial Prediction-Based Motion-Compensated Frame Rate Up-Conversion. Future Internet 2019, 11, 26.

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