In the process of data visualization, the general interpolation algorithm is used to process the image, the boundary level is usually fuzzy, and it is easy to cause a large amount of loss of image edge information, which leads to the poor overall enhancement effect of the picture. In order to solve this problem, the image edge preserving strategy is introduced into the inverse distance interpolation algorithm, and an adaptive inverse distance weighted interpolation algorithm based on image edge preserving is proposed.. On the basis of establishing the optimization direction of the image edge, the relationship between pixels in the image edge region is obtained by using the inverse distance weighted interpolation function, according to the weight drop index, the definition of the image edge is adjusted, and the smoothing parameters are set to control the smoothing effect of the algorithm, so as to achieve the best state of the overall image enhancement effect. The computer simulation image enhancement experiment evaluates the overall image enhancement effect based on the image quality measurement value of image energy spectrum and image entropy. The results show that the overall image enhancement effect after the algorithm processing is obvious, and the algorithm has outstanding advantages in terms of execution efficiency and image entropy value promotion.