Infrared background suppression method based on low-pass adaptive morphological filtering

Honglin Ji, Zijian Cui
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Abstract

Dim infrared targets often have low recognition accuracy in complex environments, because of its small size and low brightness. Therefore, this paper presents an infrared background suppression method based on low-pass adaptive morphological filtering. In this method, the infrared background noise is connected into multiple regions by low-pass filtering, the adaptive morphological mask is generated by local mean variance ratio and region growth, and then most of the background is suppressed by top-hat operation. The test results show that this method can suppress the background of infrared images and enhance the target signal.
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基于低通自适应形态学滤波的红外背景抑制方法
弱小红外目标由于体积小、亮度低,在复杂环境下往往识别精度较低。为此,本文提出了一种基于低通自适应形态学滤波的红外背景抑制方法。该方法通过低通滤波将红外背景噪声连接到多个区域,通过局部均方差比和区域生长生成自适应形态掩模,然后通过顶帽运算抑制大部分背景。测试结果表明,该方法可以抑制红外图像的背景,增强目标信号。
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