遥感异常目标的仿生非线性滤波检测.doc

中图法分类号: TP751.5 文献标识码:A 文章编号:1006-8961(年) - 论文引用格式： 遥感异常目标张学武大学工程学院213022 摘 要 ：目的 为了解决复杂下背景特征与特征导致检测结果虚警率偏高问题，复杂背景仿真数据及真实遥感数据的异常检测上有较大改善实现快速检测的同时提高了检测命中率。结论方法计算低对背景下的小尺寸异常目标较好的检测效果。 关键词 ：遥感图像；；Anomaly detector based on bionic nonlinear filter for remote sensing data Li Min, Fan Xinnan, Zhang Xuewu Collage of Internet of Thing (IOT), Hohai University, Changzhou 213022,China Abstract: Objective: Anomaly detector has become increasingly important in remote sensing data analysis and has been used in many applications, such as environmental and agricultural monitoring, geological exploration, and national defense security. According to special spectral content, an anomaly target has an obvious edge feature, which corresponds to a high frequency. By contrast, the background corresponds to a low frequency because of its smooth spectral content. Considering different spectral contents from the background, the anomaly target can be filtered out from the high frequency of the edge. A fast anomaly detector has been proposed to detect anomaly by linear filter of the spatial domain. However, texture and detail of clutter background also have the characteristic of high frequency. Linear filter has difficulty separating the anomaly from the clutter background accurately. Compared with bright background object, spatial salience of anomaly will be decreased. Furthermore, small size of anomaly will lead to subpixel anomaly, which will blur the edge feature of the target. A small anomaly target may not be successfully detected by a spatial filter. Conversely, cross analysis of a binary image reduced the complexity of computation. However, self-correlation of the large anomaly target will lead to a hollow effect in the center area. Inspired by the nonlinear filter mechanism of biotical vision, a bionic anomaly detection algorithm is proposed. Method: In the natural world, a biotical vision system can accurately detect a small moving target, even in a cluttered environment. Re