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- W992099894 abstract "To achieve restoration of high frequency information for an undersampled and degraded low-resolution image, a nonlinear and real-time processing method the radial basis function (RBF) neural network based super-resolution method of restoration is proposed. The RBF network configuration and processing method is suitable for a high resolution restoration from an undersampled low-resolution image. The soft-competition learning scheme based on the k-means algorithm is used, and can achieve higher mapping approximation accuracy without increase in the network size. Experiments showed that the proposed algorithm can achieve a super-resolution restored image from an undersampled and degraded low-resolution image, and requires a shorter training time when compared with the mulfiplayer perception (MLP) network." @default.
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- W992099894 date "2004-01-01" @default.
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- W992099894 title "Radial Basis Function Neural Network Based Super-Resolution Restoration for an Undersampled Image" @default.
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