Optical Flow Based Co-located Reference Frame for Video Compression

This paper proposes a novel bi-directional motion compensation framework that extracts existing motion information associated with the reference frames and interpolates an additional reference frame candidate that is co-located with the current frame. The approach generates a dense motion field by p...

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Veröffentlicht in:IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - PP(2020) vom: 12. Aug.
1. Verfasser: Li, Bohan (VerfasserIn)
Weitere Verfasser: Han, Jingning, Xu, Yaowu, Rose, Kenneth
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2020
Zugriff auf das übergeordnete Werk:IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Schlagworte:Journal Article
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520 |a This paper proposes a novel bi-directional motion compensation framework that extracts existing motion information associated with the reference frames and interpolates an additional reference frame candidate that is co-located with the current frame. The approach generates a dense motion field by performing optical flow estimation, so as to capture complex motion between the reference frames without recourse to additional side information. The estimated optical flow is then complemented by transmission of offset motion vectors to correct for possible deviation from the linearity assumption in the interpolation. Various optimization schemes specifically tailored to the video coding framework are presented to further improve the performance. To accommodate applications where decoder complexity is a cardinal concern, a block-constrained speed-up algorithm is also proposed. Experimental results show that the main approach and optimization methods yield significant coding gains across a diverse set of video sequences. Further experiments focus on the trade-off between performance and complexity, and demonstrate that the proposed speed-up algorithm offers complexity reduction by a large factor while maintaining most of the performance gains 
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700 1 |a Xu, Yaowu  |e verfasserin  |4 aut 
700 1 |a Rose, Kenneth  |e verfasserin  |4 aut 
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