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Curvature Interpolation Method for Image Zooming

机译:图像缩放的曲率插值方法

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We introduce a novel image zooming algorithm, called the curvature interpolation method (CIM), which is partial-differential-equation (PDE)-based and easy to implement. In order to minimize artifacts arising in image interpolation such as image blur and the checkerboard effect, the CIM first evaluates the curvature of the low-resolution image. After interpolating the curvature to the high-resolution image domain, the CIM constructs the high-resolution image by solving a linearized curvature equation, incorporating the interpolated curvature as an explicit driving force. It has been numerically verified that the new zooming method can produce clear images of sharp edges which are already denoised and superior to those obtained from linear methods and PDE-based methods of no curvature information. Various results are given to prove effectiveness and reliability of the new method.
机译:我们介绍了一种新颖的图像缩放算法,称为曲率插值方法(CIM),它基于偏微分方程(PDE),易于实现。为了最小化图像插值中出现的伪像,例如图像模糊和棋盘效应,CIM首先评估低分辨率图像的曲率。在将曲率内插到高分辨率图像域后,CIM通过求解线性化曲率方程,并结合内插曲率作为显式驱动力,从而构建高分辨率图像。在数值上已经证实,新的缩放方法可以产生清晰的锐利边缘图像,这些边缘已被去噪,并且优于从线性方法和基于PDE的无曲率信息的方法获得的图像。给出了各种结果,证明了该方法的有效性和可靠性。

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