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A Single Frame Super-Resolution Method Based on Matrix Completion

机译:基于矩阵完成的单帧超分辨率方法

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Efficiently exploring the linear relationship among neighboring pixels is a pervasive way to reconstruct high-resolution image from low-resolution one. However, it is a challenge to determine the order of linear model. According to the theory of matrix completion, we propose a single frame super-resolution algorithm by minimizing the sum of all the augmented matrices' rank, which can reflect the order of the region aware linear model. Various experiments demonstrate the images reconstructed by the proposed method have superior PSNR and visual quality, benefitting from its desirable ability of depressing the ringing noise and other artifacts.
机译:有效地探索相邻像素之间的线性关系是从低分辨率1重建高分辨率图像的普遍方式。 然而,确定线性模型的顺序是一项挑战。 根据矩阵完成理论,我们通过最小化所有增强矩阵排名的总和来提出单个帧超分辨率算法,这可以反映区域感知线性模型的顺序。 各种实验证明了所提出的方法重建的图像具有优异的PSNR和视觉质量,从而源于抑制振铃噪声和其他伪像的理想能力。

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