阈值
杂乱
恒虚警率
人工智能
计算机科学
斑点检测
对比度(视觉)
计算机视觉
人类视觉系统模型
模式识别(心理学)
分割
滤波器(信号处理)
显著性图
目标检测
图像对比度
图像(数学)
边缘检测
图像处理
雷达
电信
作者
Xiaopeng Shao,Hongwei Fan,Guangxu Lu,Jingdong Xu
标识
DOI:10.1016/j.infrared.2012.06.001
摘要
To achieve higher detection rate and lower false alarm rate in dim and small target detection, this paper proposed an improved algorithm based on the contrast mechanism of human visual system (HVS) for infrared small target detection in an image with complicated background. According to the contrast mechanism of HVS, Laplacian of Gaussian (LoG) filter is exploited to deal with the input image, which can not only suppress the background noise and clutter but also enhances the target intensity significantly. As a result it increases the contrast ratio between target and background. To further eliminate residual clutter, we process the filtered image with morphological method in all directions. True target is finally obtained by applying local thresholding segmentation to the pre-processed image. Experimental results demonstrate its superior and reliable detection performance by high detection rate and low false alarm rate.
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