Research On Image Inpainting Based On The Non-Local Means Algorithm

Image restoration is one of the important research hotspots in computer graphics, computer vision and image processing. It has great potential in many applications, especially in restoration of art, fast data transferring on the internet, computer automation, special effects, virtual reality and so on.Image inpainting is an important research topic in the area of image restoration; its objective is to restore the lost information according to around image information. Although the inpainting basics are straightforward, most inpaiting techniques published in the literature are complex to understand and implement.Fast marching method (FMM) is an efficient inpainting algorithm for level set applications, but it will cause blur problem for big damaged portions of digital images. Buades presented a new image denoising method based on the non-local means (NL-means) algorithm. In this paper, we present a new image inpainting method (FMM-NL algorithm) which uses the non-local means algorithm for texture pixes and the fast marching method for non-texture ones. Since the fast marching method can only inpaint one pix when marching, we propose a new technique for image inpainting based on the group marching method and non-local means algorithm.Originally, the inpainting methods based on partial differential equation can not be applied for texture images. However, experimental results illustrate that the new inpainting method based on the non-local means algorithm is very simple to implement, and can well solve the blur problem especially for texture image.