文章基本信息

标题：Optimum Patch Selection Using GA in Exemplar Based Image In-painting
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作者：Seema Kumari Singh ; Prof J.V Shinde
期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2015
卷号：6
期号：2
页码：990-997
出版社：TechScience Publications
摘要：Image in-painting is the art of restoring lost and selected parts of an image based on the background information in such a way so that the change is not observed by the observer. Image In-painting is very important and emerging field of research in image processing. Image Inpainting algorithm have numerous applications such as rebuilding of damaged photographs & films, heritage preservation, removal of superimposed text, removal/replacement of unwanted objects, red eye correction, image coding etc.. In this paper, we are using GA based patch selection approach for Exemplar based Image inpainting using Multiscale graph-cut. In order to improve the computational time and also the acceptable quality of the image, Genetic algorithm is proposed here. Graph cut algorithm is used to solve the problem of energy minimization. Our experiments show how well the proposed algorithm performs compared with the other recent algorithms.
关键词：Image in-painting; graph-cut; Genetic Algorithm;Exemplar; Gradient; mutation