An adaptive image interpolation algorithm is presented. This method will enable the interpolation kernel to be varied based on the local image information. The criteria for the variation is a decision mechanism which discriminates the text or high contrast areas from the graphic or soft contrast areas. Upon the decision, the algorithm will apply the appropriate interpolation kernel functions to interpolate the data. The interpolation kernel for text area utilizes a 2 X 2 convolution kernel using a fifth (5th) order interpolation polynomial. The graphic areas of the image file will use a 4 X 4 kernel with a cubic spline function. The objective of the method is to reduce the aliasing or ringing effect associated with the interpolation of high spatial frequency (text) areas of the image file. In order to identify the two areas (text vs graphic) a 4 X 4 pixel window is chosen. The sample mean and deviation of this window is calculated. Further the sample mean and deviation of the inner 2 X 2 block of the 4 X 4 window is also determined. The ratio of the sample deviation of 2 X 2 to the sample deviation of 4 X 4 window is then compared to a preset threshold discriminator level.