An efficient image inpainting algorithm based on a modified Gray-Scott model

In this paper, we proposes an image inpainting algorithm based on the modified Gray-Scott (GS) model. We have added a fidelity term to control the edge and stability of pixel value evolution during the image inpainting process. We verify the effectiveness and robustness of the proposed model through various experiments. By constructing binary images and complex pixel images with a bit depth of 8, we demonstrate the effectiveness of the model on damaged images with Gaussian noise and locally missing pixels. Additionally, we use metrics such as root mean square error (RMSE) and peak signal-to-noise ratio (PSNR) to evaluate the modified GS model. We compared the model with other methods in terms of both visual and computational metrics, and our proposed model outperforms other methods.