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Image interpolation is an important image processing operation applied in diverse areas ranging from computer graphics, rendering, editing, medical image reconstruction, to online image viewing. Image interpolation techniques are referred in literature by many terminologies, such as image magnification etc. In this paper, we proposed an improved image interpolation algorithm based on wavelet neural network theory and shown its efficacy. Numerical experiments on real images show that this method can eliminate efficiently zigzagging and edge blurring artifacts.