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首页> 外文期刊>Pattern Recognition: The Journal of the Pattern Recognition Society >Infrared small target detection via adaptive M-estimator ring top-hat transformation
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Infrared small target detection via adaptive M-estimator ring top-hat transformation

机译:通过自适应M估计环顶帽变换的红外小目标检测

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摘要

Top-Hat transformation is an essential technology in the field of infrared small target detection. Many modified Top-Hat transformation methods have been proposed based on the different structure of structural elements. However, these methods are still hard to handle the dim targets and complex background. It can be summarized as two reasons, one is that the structural elements cannot suppress the background adaptively due to the fixed value of structural elements in image. Another is that simple structural element cannot utilize the local feature for target enhancement. To overcome these two limitations, a special ring Top-Hat transformation based on M-estimator and local entropy is proposed in this paper. First, an adaptive ring structural element based on M-estimator is used to suppress the complex background. Second, a novel local entropy is proposed to weight structural element for capturing local feature and target enhancement. Finally, a comparison experiment based on massive infrared image data (more than 500 infrared target images) is done. And the results demonstrate that the proposed algorithm acquires better performance compared with some recent methods. (C) 2020 Elsevier Ltd. All rights reserved.
机译:Top-Hat变换是红外小目标检测领域的一项关键技术。基于结构单元的不同结构,人们提出了许多改进的Top-Hat变换方法。然而,这些方法仍然难以处理弱小目标和复杂背景。这可以归结为两个原因,一是由于图像中结构元素的固定值,使得结构元素无法自适应地抑制背景。另一个原因是,简单的结构元素不能利用局部特征来增强目标。为了克服这两个局限性,本文提出了一种基于M估计和局部熵的特殊环顶帽变换。首先,采用基于M估计的自适应环形结构元素来抑制复杂背景。其次,提出了一种新的局部熵来加权结构元素,以获取局部特征和增强目标。最后,基于大量红外图像数据(500多幅红外目标图像)进行了对比实验。实验结果表明,与现有的一些算法相比,该算法具有更好的性能。(C) 2020爱思唯尔有限公司版权所有。

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