一种基于BEMD和局部逆熵的新型红外小目标检测方法
投稿时间:2016-07-07  最后修改时间:2016-09-26  点此下载全文
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作者单位E-mail
解婷 华中科技大学 自动化学院 easyma126@126.com 
陈忠 华中科技大学 自动化学院 easyma126@126.com 
马荣毅 华中科技大学 自动化学院  
基金项目:1.面向对象高分辨率遥感图像信息提取技术研究(国家自然科学基金青年基金40801164);2. 低信噪比红外弱小目标TLD跟踪技术研究(航天支撑基金CAST2015);3.基于视觉显著性港口舰船目标提取新技术研究(高效联合创新基金CALT2015)
中文摘要:与其它目标检测相比,由于多种因素例如低信噪比,低对比度,小尺寸,缺乏目标的形状和纹理信息,尤其是在复杂背景条件下,检测红外小目标的检测会更加的困难。在实践中,一种基于同组过滤器(PGF),二维经验模式分解(BEMD)和局部逆熵(LIE)的新型红外小目标检测方法被提出来解决前面所提到的困难。其中PGF被用来消除噪声和改善初始图像的信噪比;BEMD算法可以有效的估计背景并将背景从原始图像中移除;LIE的主要作用是分解本征模态函数(IMFs)。实验结果表明,新的方法可以有效且准确地提取小目标。
中文关键词:红外小目标  目标检测  局部逆熵  BEMD
 
A Novel Method of infrared small target detection based on BEMD and LIE
Abstract:Compared to other targets, it is more difficult to detect infrared small targets due to several aspects such as the low signal to noise ratio, low contrast, small size, the lack of shape and texture information of the targets, especially under complex background. In this paper, a novel infrared small target detection method based on peer group filter (PGF), bi-dimensional empirical mode decomposition (BEMD) and local inverse entropy (LIE) is proposed to overcome these difficulties. The PGF is implemented to remove the noise and improve the signal-to-noise ratio of the initial image. Our proposed BEMD algorithm is able to estimate the background effectively and get the target image by removing the background from the original image and segmenting the Intrinsic Mode Functions (IMFs) making use of the local inverse entropy. Experimental results demonstrate that the novel method can extract the small targets validly and accurately.
keywords:Infrared small target  Local inverse entropy  target detection  BEMD
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