Nonparametric Complex Background Prediction Algorithm Using FCM Clustering for Dim Point Infrared Targets Detection

摘要：

A nonparametric background prediction algorithm using fuzzy c-means (FCM) clustering is proposed to enhance the detection of dim small infrared targets in image data. The target of interest is assumed to have a very small spatial spread, and is obscured by heavy background clutter. The input image data is firstly segmented using FCM clustering, and then the nonparametric regressive method is applied to predict background in each cluster respectively. Subsequently the background is subtracted from the input data, leavingcomponents of the target signal in the residual noise.Experiment results show better detecting performance for the output data by the algorithm of this paper than by other traditional methods.

作者: Honggang Wu Xiaofeng Li Yuebin Chen Zaiming Li

作者单位: School of communication and information engineering University of Electronic Science and Technology Chengdu, Sichuan, China

会议类型: 国际会议

会议名称: 2006 International Conference on Communications,Circuits and Systems(第四届国际通信、电路与系统学术会议)

会议地点: 广西桂林

会议语种:英文

页码: 222-225

在线出版日期: 2006-06-25（万方平台首次上网日期，不代表论文的发表时间）