一种改进的基于多尺度斑块的红外小目标检测对比度方法

Ye Tang, Kun Xiong, Chunxi Wang
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引用次数: 1

摘要

针对现有红外小目标检测方法背景抑制不足、多目标检测能力弱,导致红外搜索跟踪系统虚警率高、遗漏系数高的问题,提出了一种融合修正各向异性扩散系数与多尺度斑块对比测度(ADMPCM)的红外小目标检测方法。将局部区域内4个不同方向的局部对比值应用到修正的各向异性扩散系数方程中,最终滤波结果为4个方程的最小函数值。不同寻常的实验结果表明,与同类检测方法相比,单目标检测任务的背景抑制系数平均提高了2.95倍,信杂比增益平均提高了6.17倍,多目标检测任务的信杂比增益平均提高了10.49倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Improved Multiscale Patch-Based Contrast Measure for Small Infrared Target Detection
Aiming at the problems of insufficient background suppression and weak multi-target detection abilities of existing infrared small target detection methods, which lead to high false alarm rate and high omission factor of infrared search and track system, an infrared small target detection method fusing modified anisotropic diffusion coefficients with multiscale patch-based contrast measure (ADMPCM) was proposed. The local contrast values of four different directions in the local area are applied into the modified anisotropic diffusion coefficient equation, and the final filtering result is the minimum function value of the four equations. Extraordinary experimental results revealed that, in average, background suppression factor increased 2.95 times, signal-to-clutter ratio gain increased 6.17 times on single-target detection task and 10.49 times on multi-target detection task, respectively, compared with similar detection methods.
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