Image Zooming Algorithm and Implementation based on Self-Snake Model
Ren Xiao-bi · Journal of Anyang Normal University · 2015
Image resolution ratio is one of the key factors that determine the image quality. There are currently many image zooming algorithms,although there are problems referred to blurred edges and jagged edges after the images have been magnified in most of the algorithms. In order to solve the problem which can be seen as image noise,filtering is adopted to deal with denoising. In this article,the self-snake model adopted is a very efficient de-noising model,it has outstanding results in de-noising and image edge preservation.Therefore,this article intends to apply the edge effects of self-snake model in the process of magnifying the images,along with added process of modification to enhance the restored image quality. The programming experiment has been carried out in the final part,tested and verified the favorable performance compared to traditional approaches.