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Biomedical image interpolation based on multi-resolution transformations

机译:基于多分辨率变换的生物医学图像插值

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摘要

We present a novel feature-based image interpolation approach. Two continuous maps for the image domain are constructed via an L2-gradient flow based on their multi-resolution representations so that the features of the given images are matched at multiple scales. The flow equation is efficiently solved using a finite element method in the bicubic B-spline vector-valued function space. The interpolated images are then obtained from the domain maps at any sampling rate. Experimental results show that our interpolation approach is effective, capable of capturing image features from large to small. It yields continuously and uniformly deformed in-between images.
机译:我们提出了一种新颖的基于特征的图像插值方法。基于L2梯度流的多分辨率表示形式,构造了两个连续的图像域图,以使给定图像的特征在多个比例上匹配。在双三次B样条向量值函数空间中使用有限元方法有效地求解了流动方程。然后以任意采样率从域映射中获得内插图像。实验结果表明,我们的插值方法是有效的,能够捕获从大到小的图像特征。它在图像之间连续且均匀地变形。

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  • 作者单位

    Institute of Computational Mathematics, Academy of Mathematics and System Sciences, Chinese Academy of Sciences, Beijing, China;

    Institute of Computational Mathematics, Academy of Mathematics and System Sciences, Chinese Academy of Sciences, Beijing, China;

    Institute of Computational Mathematics, Academy of Mathematics and System Sciences, Chinese Academy of Sciences, Beijing, China;

    Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, PA, US;

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