Abstract
A neural network based interpolation scheme using the local spatial properties of the source image for image enlargement is proposed. The local spatial properties that are used for neural network training include the neighbor pixels gray values, the average value and the gray value variations between neighbor pixels in the selected region. Gaussian radial basis function neural network is used for image local spatial properties pattern learning and regression estimation for image interpolation. The trained neural network is used to estimate the gray values of unknown pixels using the known neighbor pixels and local spatial properties information. Some interpolation experiments demonstrate that the proposed approach is superior to linear, cubic and other neural network and support vector machines based interpolation approaches.
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