摘要
红外图像中的微弱目标检测与跟踪是数字图像处理领域中的研究热点。针对红外图像中微弱目标灰度的统计特点以及模糊神经网络在自适应噪声消除的应用,提出一种基于增强型动态模糊神经网络算法用于红外图像噪声消除。经过自适应噪声消除后,可有效的有自动阈值门限分割法进行微弱目标检测。
Detection and track of dim and small target in infrared images are focused in the area of digital image processing research. According to dim and small targets density statistical characteristics in infrared images and the application of fuzzy neural networks in self-adaptive noise elimination, a new method based on enhanced dynamic fuzzy neural networks is proposed, using on eliminating in- frared images noise. After self-adaptive noise elimination, self-adaptive threshold can be adopted effectively for dim small target detection.
出处
《微计算机信息》
2010年第5期42-43,49,共3页
Control & Automation
关键词
红外图像
徽弱目标
自适应
目标检测
动态模糊神经网络
Infrared image
Dim and small target
Target detection
serf-adaptive
Dynamic Fuzzy Neural Networks
