Edge-driven Image Interpolation using Adaptive Anisotropic Radial Basis Functions

This paper investigates the image interpolation problem, where the objective is to improve the resolution of an image by dilating it according to a given enlargement factor. We present a novel interpolation method based on Radial Basis Functions (RBF) which recovers a continuous intensity function from discrete image data samples. The proposed anisotropic RBF interpolant is designed to easily deal with the local anisotropy in the data, such as edge-structures in the image. Considering the underlying geometry of the image, this algorithm allows us to remove the artifacts that may arise when performing interpolation, such as blocking and blurring. Computed examples demonstrate the effectiveness of the method proposed by visual comparisons and quantitative measures.

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