Impainting by Restoring Image Gradients

Impainting is used both to improve the visual perception of an image and in classical problems of recognition and robotics to remove irrelevant information from an image. Modern impainting methods of reconstruction drawing use neural networks. However, these approaches are plagued with disadvantages that prevent these algorithms from being used in practical applications of computer vision. The authors have proposed in their recent paper an impainting method based on a non-local mean (NLM) filter that outperforms other conventional image processing methods in terms of peak signal-to-noise ration (PSNR). However, this algorithm may create artifacts at the boundaries of the rendering zones that distort visual perception. In this article, we propose to draw not the image, but the gradients of the image restored and only then restore the image itself, maintaining in this way connectivity at the border of the rendering areas. This method eliminates most of the artifacts that arise when using the previously proposed method, and also surpasses it in terms of the recovery accuracy assessed using the PSNR criterion.