Image Restoration Based on Parallel GA and Hopfield NN

摘要：

There is distortion phenomenon in image emerge, transmit and record. Image restoration is a process which recover bad image into original image. When we use genetic algorithm for image restoration, there will be premature problem. The paper discusses a new algorithm for image restoration based on combination of parallel genetic algorithm with Hopfield neural network, take the advantage of parallel GA parameter selection and then use Hopfield NN to train sample efficiently. Experiments demonstrate that this optimization method in this paper will overcome premature problem and run more rapidly, as a result obtain a better recovery image.

关键词： Image Restoration Genetic Algorithm Hopfield Neural Network Optimization Algorithm

作者: Tingting Sun Xisheng Wu

作者单位: School of Information Technology Jiangnan University Wuxi, P.R.China

会议类型: 国际会议

会议名称: 第九届分布式计算及其应用国际学术研讨会

会议地点: 香港

会议语种:英文

页码: 565-567

在线出版日期: 2010-08-12（万方平台首次上网日期，不代表论文的发表时间）