摘要
本文采用小波变换和形态Top Hat滤波相结合的方法抑制红外图像的混合噪声及大面积的背景干扰 ,减少图像模糊和增强目标 ;通过选择适当的结构元素进行系列形态组合运算 ,去掉虚警点而获得少量候选目标 ;搜索局部极大值并确定阈值 ,分离出真正的目标 .实验结果表明 ,该方法能有效检测和分割出低信噪比复杂自然背景红外图像中的目标 .
Approach proposed in this paper combines wavelet transform with morphology Top-Hat filter to suppress the mixed noise and the large-scale clutter caused by background in the infrared images. This process can decrease the blur of the images and enhance the targets. Then, proper structuring elements are selected to execute serial morphology operations to discard most false alarms, through which a few potential small targets can be obtained. Eventually, the real target can be segmented through searching maximal grayscale and assigning a threshold. The experimental results show that the method can effectively detect and segment the target in a low SNR infrared image with the complicated nature background.
出处
《信息与控制》
CSCD
北大核心
2004年第1期107-111,共5页
Information and Control
基金
中国科学院国防科技创新基金资助项目 (CXJJ -65 )
