An image inpainting method based on image retrieval

Image inpainting refers to the process of reconstructing the damaged image or removal of unwanted objects in the image. We need to take the most appropriate way of inpainting the image to its original state, while ensuring that the result achieves the best artistic effect. There are some methods commonly used, such as method based on PDE or based on texture synthesis. But in cases that the damaged region is too large or a semantic fragment is completely missed, those old methods cannot do a good job. Rather than inpainting within the original image data, a way of inpainting using image content from other pictures will do help. As long as the improvement of research in image retrieval, we hope to take advantage of the good results by image retrieval with particular criteria. With the image patches from the image retrieval results, we can do a better inpainting and achieve the result more in line with the visual effects. This paper shows the algorithm and experiment results show the high efficiency and quality of the algorithm. And the unexpected result due to the random computation shows its creative accomplishment.