%0 Journal Article
%T A Parallel Genetic Algorithm for Image Super-resolution Restoration<br>基于并行遗传算法的图像超分辨率复原
%A LIU Zhi-jun
%A DING Ming-yue
%A ZHOU Cheng-ping
%A LIU Mai-li
%A <br>刘志军
%A 丁明跃
%A 周成平
%A 刘买利
%J 中国图象图形学报
%D 2004
%I 
%X The technique of image super-resolution restoration makes it possible that high resolution images could be restored from low resolution images recorded by low resolution sensors. super-resolution restoration algorithms may be divided into two classes, particularly frequency domain and spatial domain. All frequency domain approaches made use of the aliasing effect; spatial domain algorithms there are mainly three approaches, i.e. Iterative Backward Projecting(IBP), Projection Onto Convex Sets(POCS) and Bayesian methods. In this paper, a parallel genetic framework algorithm for image (sequence) super-resolution restoration is presented . The parallelism of the real-valued genetic algorithm based on the island model enables better integration of the information of the multiple frame images. Especially with the iterative method of other super-resolution algorithms being the mutation operator, the convergence of the genetic searching in the solution space is fast. The experiments demonstrate that the proposed algorithm is efficient and applicable.
%K Super-resolution
%K Image restoration
%K Real-valued genetic algorithm
%K Island model<br>超分辨率
%K 图像复原
%K 实值遗传算法
%K 岛模型
%K 并行遗传算法
%K 退化模型
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D06194629680C940ACE75262F54B9D85&aid=C057840E3ECF740D&yid=D0E58B75BFD8E51C&vid=9CF7A0430CBB2DFD&iid=CA4FD0336C81A37A&sid=95D537AC89B28832&eid=68D88C2FCF9C3098&journal_id=1006-8961&journal_name=中国图象图形学报&referenced_num=8&reference_num=8