Abstract
In this paper, a novel edge-oriented neural-network-based adaptive interpolation scheme for natural image is proposed. An image analysis module is used to classify pixels of the input image into non-oriented class and oriented class. The bilinear interpolation is used to interpolate the non-oriented regions and a neural network is proposed to interpolate the oriented regions. High-resolution digital images along with supervised learning algorithms can be used to automatically train the proposed neural network. Simulation results demonstrate that the proposed new resolution enhancement algorithm can produce higher visual quality of the interpolated image than the conventional interpolation methods.
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