2017/12/26 by Mojtaba Akbari, Majid Mohrekesh, Akbari, Mojtaba +5
Engineering · #FOS: Electrical engineering #Image and Video Processing (eess.IV) #eess.IV #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1712.09236
arxiv created 2018/01/01 · arxiv updated 2018/01/03
Image inpainting refers to filling missing places in images using neighboring pixels. It also has many applications in different tasks of image processing. Most of these applications enhance the image quality by significant unwanted changes or even elimination of some existing pixels. These changes require considerable computational complexities which in turn results in remarkable processing time. In this paper we propose a fast inpainting algorithm called RIBBONS based on selection of patches around each missing pixel. This would accelerate the execution speed and the capability of online frame inpainting in video. The applied cost-function is a combination of statistical and spatial features in all neighboring pixels. We evaluate some candidate patches using the proposed cost function and minimize it to achieve the final patch. Experimental results show the higher speed of 'Ribbons' in comparison with previous methods while being comparable in terms of PSNR and SSIM for the images in MISC dataset.