Image interpolation plays a vital role in image processing. A new image interpolation algorithm based on a rational fractal function is proposed to improve the quality of texture image magnification. This method is combined with a previous rational function interpolation algorithm. For input image preprocessing

a median filter and histogram equalization are utilized. The texture and smooth areas in the image are classified through the blanket method and the multi-scale fractal characteristic value of the image. Finally

a rational fractal interpolation function is employed for the texture region

and a rational interpolation function is adopted for the smooth area. An optimization technique is then utilized to further modify the interpolation model

which is proven to be effective. A rational fractal interpolation algorithm is proposed in this article. For common images

the quality of interpolation approximates that of NEDI and NARM. For texture images

the proposed method is highly competitive not only in PSNR and SSIM but also in visual effect. This article presents a novel image interpolation method based on a rational fractal function. Experimental results demonstrate that the proposed method exhibits competitive performance

especially in terms of image details and texture features.