  There are many methods for image enhancement. Image inpainting is one of them
which could be used in reconstruction and restoration of scratch images or
editing images by adding or removing objects. According to its application,
different algorithmic and learning methods are proposed. In this paper, the
focus is on applications, which enhance the old and historical scratched
images. For this purpose, we proposed an adaptive spline interpolation. In this
method, a different number of neighbors in four directions are considered for
each pixel in the lost block. In the previous methods, predicting the lost
pixels that are on edges is the problem. To address this problem, we consider
horizontal and vertical edge information. If the pixel is located on an edge,
then we use the predicted value in that direction. In other situations,
irrelevant predicted values are omitted, and the average of rest values is used
as the value of the missing pixel. The method evaluates by PSNR and SSIM
metrics on the Kodak dataset. The results show improvement in PSNR and SSIM
compared to similar procedures. Also, the run time of the proposed method
outperforms others.
