16 September 2016 Temporal super-resolution based on pixel stream and featured prior model for motion blurred single video
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Abstract
Single-video-based temporal super-resolution reconstruction (SRR) can get rid of constraints imposed on multiple-video-based temporal SRR, including device scarcity, temporal synchronization, complicated registration, and high cost. But frame interpolation in single-video-based temporal SRR cannot deblur well, and the selection or determination related to interpolation function has a lack of evidence, which reduces the fidelity. Additionally, the subsequent spatial deblurring is suboptimal for the motion blur in video because the formation of the motion blur is different from that of the spatial blur. This paper proposes a temporal SRR based on pixel stream and featured prior model to increase the frame rate and the definition of motion blurred single video. The proposed temporal SRR views the single video as a bundle of pixel streams and implements maximum-
© 2016 SPIE and IS&T
Feng Xu, Mengxi Xu, Defu Jiang, Jianqiang Shi, Aiye Shi, "Temporal super-resolution based on pixel stream and featured prior model for motion blurred single video," Journal of Electronic Imaging 25(5), 053011 (16 September 2016). https://doi.org/10.1117/1.JEI.25.5.053011 . Submission:
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