一种灵活放大的快速超分辨率从粗到精的方法

Zhichao Fu, Tianlong Ma, Liang Xue, Yingbin Zheng, Hao Ye, Liang He
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引用次数: 0

摘要

我们对自然图像进行快速的单图像超分辨率和灵活的放大。提出了一种新的粗到精的超分辨率框架,将放大倍数分解为最大整数分量和商。具体来说,我们的框架嵌入了一个轻量级的高端网络,用于整数比例因子的超分辨率,然后是细粒度网络,用于指导特征图的插值,并生成超分辨率图像。与以往的柔性放大超分辨率方法相比,该框架实现了计算复杂度和性能之间的平衡。我们在标准基准上使用从粗到精的框架进行了实验,并证明了其在有效性和效率方面优于以前的方法。
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A Coarse-to-fine Approach for Fast Super-Resolution with Flexible Magnification
We perform fast single image super-resolution with flexible magnification for natural images. A novel coarse-to-fine super-resolution framework is developed for the magnification that is factorized into a maximum integer component and the quotient. Specifically, our framework is embedded with a light-weight upscale network for super-resolution with the integer scale factor, followed by the fine-grained network to guide interpolation on feature maps as well as to generate the super-resolved image. Compared with the previous flexible magnification super-resolution approaches, the proposed framework achieves a tradeoff between computational complexity and performance. We conduct experiments using the coarse-to-fine framework on the standard benchmarks and demonstrate its superiority in terms of effectiveness and efficiency over previous approaches.
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