Image Interpolation using Feedforward Neural Network

H. Aokage, K. Kameyama, and K. Wada (Japan)


digital image, resolution conversion, high quality, artificial neural network, feedforward network


As various kinds of output devices emerged, such as high resolution printers or a display of PDA(Personal Digital Assistant), the importance of high-quality resolution conversion has been increasing. This paper proposes a new method for enlarging image with high quality. One of the largest problems on image enlargement is the exaggeration of the jaggy edges. To remedy this problem, we propose a new interpolation method, which uses artificial neural network to determine the optimal values of interpolated pixels. The experimental results are shown and evaluated. The effectiveness of our methods is discussed by comparing with the conventional methods.

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