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There are many methods for image enhancement. Image inpainting is one of themwhich could be used in reconstruction and restoration of scratch images orediting images by adding or removing objects. According to its application,different algorithmic and learning methods are proposed. In this paper, thefocus is on applications, which enhance the old and historical scratchedimages. For this purpose, we proposed an adaptive spline interpolation. In thismethod, a different number of neighbors in four directions are considered foreach pixel in the lost block. In the previous methods, predicting the lostpixels that are on edges is the problem. To address this problem, we considerhorizontal 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 usedas the value of the missing pixel. The method evaluates by PSNR and SSIMmetrics on the Kodak dataset. The results show improvement in PSNR and SSIMcompared to similar procedures. Also, the run time of the proposed methodoutperforms others.

Image Inpainting by Adaptive Fusion of Variable Spline Interpolations