首页> 外文会议>Conference on Infrared Materials, Devices, and Applications; 20071112-15; Beijing(CN) >Analysis of selection of structural element in mathematical morphology with application to infrared point target detection
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Analysis of selection of structural element in mathematical morphology with application to infrared point target detection

机译:数学形态学中结构元素的选择分析及其在红外点目标检测中的应用

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Low signal-to-noise ratio and complex background make the point target detection from infrared image a challenging and difficult problem. Combining the filtering characteristic of opening operation of mathematical morphology and the technique of background prediction, this paper presents a point target detection algorithm based on mathematical morphology, including analytic expressions for the detection algorithm. The selection of structural element is the key of mathematical morphology. The analyzing method of selection of structural element is presented. This paper mainly analyzes and compares the different performances produced by four kinds of structural elements having different size and shape, when these structural elements process the different components of complex background and point target. The analyzing and comparing methods focus on the curves generated by plotting the samples of image in row in which the point target exists. This analyzing method of selection of structural element is effective. The experiment results of detection algorithm using four kinds of structural elements to respectively process the infrared point target image are also presented and analyzed, including the probability of detection and the number of false targets.
机译:低信噪比和复杂的背景使红外图像中的点目标检测成为一个具有挑战性和困难的问题。结合数学形态学开放运算的滤波特性和背景预测技术,提出了一种基于数学形态学的点目标检测算法,包括该算法的解析表达式。结构元素的选择是数学形态学的关键。提出了结构元件选择的分析方法。本文主要分析比较四种尺寸和形状不同的结构元件在处理复杂背景和目标点的不同成分时产生的不同性能。分析和比较方法着重于通过绘制图像样本在点目标所在的行中绘制而生成的曲线。这种选择结构元件的分析方法是有效的。提出并分析了使用四种结构元素分别处理红外点目标图像的检测算法的实验结果,包括检测概率和错误目标的数量。

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