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An Efficient Method of Small Targets Detection in Low SNR

机译:低信噪比的有效小目标检测方法

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摘要

In this paper, an efficient method based on nonlinear adaptive filtering is proposed to detect the small IR target of low SNR under the complex background. The morphologic filter can be constructed firstly based on the IR radiation traits of low SNR small targets in the complex background and then a morphological method is used to eliminate the influence of the unbalance background to the image segmentation. Next an algorithm of adaptive threshold segmentation is adopted in order to select the small moving target and the noise points. Finally,on the basis of image sequences, the satisfactory targets detection is accomplished after eliminating wrong point targets. The method presented in this paper can effectively suppress the noise and the air background of the original image, enhance the ability of point target detection in single frame.
机译:本文提出了一种基于非线性自适应滤波的有效方法来检测复杂背景下低信噪比的小红外目标。可以首先根据复杂背景下低信噪比小目标的红外辐射特性构造形态滤波器,然后采用形态学方法消除不平衡背景对图像分割的影响。接下来,采用自适应阈值分割算法以选择小的运动目标和噪声点。最后,基于图像序列,在消除错误的点目标之后,完成了令人满意的目标检测。本文提出的方法可以有效抑制原始图像的噪声和空气背景,增强单帧点目标检测的能力。

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