An Iterative Image Inpainting Method Based on Similarity of Pixels Values

Image inpainting is a process of completion of missing places by using other undamaged sections of the image or removal of unwanted objects of the image. In this study, we propose a novel image inpainting method. This method constitutes an essential place in image processing. This proposed method fills the corrupted area by using similarity of the boundary pixels values around that corrupted regions in every iteration step. Afterwards, to evaluate image inpainting quality of the proposed method, we use Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity (SSIM) metrics and present some visual results. The acquired results show that our proposed inpainting method gives an outstanding performance to fill the corrupted areas and to remove objects. We also discuss the need for further research.