摘要
采用维纳自适应滤波,抑制随机噪声和高斯噪声;利用Otus阈值法分割图像,确定海天线和目标潜在区;利用Top Hat算子进行形态滤波处理,抑制平缓变化背景并保留高亮度区的目标和强噪声;选择结构元素进行形态开运算,去掉细小的背景杂波干扰;针对远距离舰艇小目标总是出现在海天线附近以及红外目标灰度高于其邻域背景的特点,确定阈值即可分离出真正的目标。实验结果表明,该方法可以较好地抑制海浪、云层等背景的干扰,能有效检测复杂海面背景中的红外小目标。
The proposed approach adopts adaptive filter to suppress random noise and Gauss's noise so as to enhance the SNR. Then, Otus's threshold method is used to segment the image and locate the sea-sky-line, through which the target potential area can be determinated. A mathematical morphology filter, Top-Hat operator, is employed to execute filtering to restraint the background contribution and maintain the small target in high brightness area. By choosing proper structural element, an open filter is executed to discard small false alarms. Eventually, the real small target can be segmented through searching maximal value in the target potential area nearby the sea-sky-line and assigning threshold. The experimental results show that the method can reject the clutter caused by waves and clouds and effectively detect and segment IR small target in the complicated sea background.
出处
《红外与激光工程》
EI
CSCD
北大核心
2003年第6期590-593,604,共5页
Infrared and Laser Engineering
基金
中国科学院国防科技创新基金支持项目(CXJJ 65)
关键词
红外小目标
数学形态学
目标检测
图像分割
海面背景
IR small target
Mathematical morphology
Target detection
Image segmentation
Sea background
