基于IHBF的增强局部对比度红外小目标检测方法

IHBF-Based Enhanced Local Contrast Measure Methodfor Infrared Small Target Detection

  • 摘要: 针对非均匀背景下红外小目标检测率低的问题,本文引入人眼视觉系统对比度机制,提出一种基于改进高提升滤波(improved high boost filter,IHBF)的增强局部对比度红外小目标检测方法。首先,根据小目标的频域特性,通过IHBF运算提升高频信号同时,剔除含有背景的低频信号;然后,提出增强局部对比度方法构建比差联合形式的算子,进一步增强目标与背景间的对比度,获得最优显著图;最后,采用自适应阈值分割技术获取真实目标。仿真结果表明:相对于现有的局部对比度算法,所提方法在检测率、虚警率等方面更具优势,是非均匀背景下检测红外小目标的一种有效方法。

     

    Abstract: Inspired by the contrast mechanism of the human visual system (HVS), this study proposed an improved high boost filter (IHBF)-based enhanced local contrast measurement method for solving the low detection rate of infrared (IR) small targets with a non-homogeneous background. First, based on the frequency characteristics of the small target, the IHBF operation was used to discard the low-frequency signal containing the background. An enhanced local contrast measure method was proposed to construct the contrast operator of the ratio-difference joint form. Thus, the target contrast can be enhanced further to obtain an optimal saliency map. Finally, the adaptive threshold technology was used to extract small targets. The simulation results demonstrate that compared with existing local contrast algorithms, the proposed method is better in terms of detection rate and false alarm rate and is an effective method for detecting IR small targets in non-homogeneous backgrounds.

     

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