![]() If an incomplete image contains a large number of missing pixels (e.g. When only one incomplete image is available, the missing regions are relatively large but their texture can be recovered from surrounding regions, then the texture synthesis methods are usually the most efficient. The issue of image completion has been extensively developed for a few dozen years and many computational methods exist to tackle various image completion problems. ![]() ![]() However, Kriging and RBF interpolation give better results both for numerical data and visual evaluation for image in-painting problems with large area losses. According to the results obtained from the study, the absolute superiority of the methods against each other was not observed. Errors and noise generated on the colour and grayscale formats of some of the commonly used standard images in the literature were corrected by using Cubic, Kriging, Radial based function and High dimensional model representation approaches and the results were compared using standard image comparison criteria, namely, PSNR (peak signal-to-noise ratio), SSIM (Structural SIMilarity), Mean Square Error (MSE). This study was designed to compare the interpolation algorithms used in image in-painting in the literature. ![]() Interpolation and internal painting are one of the basic approaches in image internal painting, which is used to eliminate undesirable parts that occur in digital images or to enhance faulty parts. ![]()
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