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基于复滤波器组的红外弱小目标检测算法 被引量:2

Dim and small target detection based on complex filter bank
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摘要 为了有效抑制复杂背景的干扰,降低复杂背景所带来的虚警,提高目标检测的信噪比,提出了一种基于复滤波器组的红外弱小目标检测算法。分析了复杂背景下带有弱小目标的红外图像中复杂背景和弱小目标图像各自的频谱特性,并引入了分频段处理的思想。比较了各种滤波器的性能,并选用了基于复小波的滤波器组,用该滤波器组将红外弱小目标图像分解到各个子频域;对分解后的各频段图像分别进行基于罗宾逊滤波的目标检测处理,提取各频段图像中的奇异点;根据目标图像和背景图像的频谱特性的定量分析结果,选取合适的权值,将各频段检测的结果进行加权融合,得到最终的处理效果。实验结果表明:弱小目标检测方法较之于传统的不分频段的高通滤波处理方式可以获得更高的信噪比,目标得到明显的增强,背景杂波得到更有效的抑制,各项探测指标均更优。 In order to suppress complex background,an improved detection algorithm based on complex filter bank is presented for dim-small target under infrared background clutter.First,the spectrum characteristics of both the complex background image and the target image are analyzed,and the idea of sub-band processing is presented.Then after the comparison filters,the complex filter bank is adopted to decompose the infrared image with dim-small target into sections of different frequency bands.Next,the Robinson filter algorithm is used to process the decomposed sub-band images for extracting target.And finally these images are integrated with the method of weighting.The targets in the final processed image are enhanced notably and the backgrounds are suppressed effectively.The experimental results show that the proposed method is more effective than the traditional high-pass filter algorithm and can obtain higher signal noise ratio.
出处 《强激光与粒子束》 EI CAS CSCD 北大核心 2011年第10期2583-2588,共6页 High Power Laser and Particle Beams
基金 南京理工大学研究基金项目(2010ZDJH12)
关键词 图像处理 红外技术 目标检测 复滤波器组 复滤波器 image processing infrared technique target detection complex filter bank complex filter
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