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An efficient method to reduce computational cost of improved super-resolution method

机译:一种降低改进超分辨率方法计算成本的有效方法

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In this paper, we propose a method to efficiently reduce computational cost of the improved super-resolution method that achieves dense motion estimation using overlapped block matching. We focus on statistics of motion vectors allocated to a small cell, and conjoin the calculation for same motion vectors in the optimization process. This method can reduce the entire computational cost up to 29.9 ∼ 49.1% depending on a given video sequence in the case that maintains the original performance of the improved super-resolution method completely. If we relax the constraint that preserves the original performance, we can further reduce computational cost up to 20.7 ∼ 27.8% without serious deterioration of the quality of reconstructed images.
机译:在本文中,我们提出了一种有效地降低了通过重叠块匹配实现了实现了致密运动估计的改进超分辨率方法的计算成本的方法。我们专注于分配给小型电池的运动矢量的统计数据,并在优化过程中同一运动向量的计算。此方法可以根据完全保持改进的超分辨率方法的原始性能,将整个计算成本降低到29.9〜49.1%。如果我们放宽保留原始性能的约束,我们可以进一步降低计算成本高达20.7〜27.8%,而不会严重恶化重建图像的质量。

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