摘要
为提高目标检测概率,针对复杂的地面目标红外亚图像,提出了一种以最大类间方差法为基础的自适应阈值图像分割方法.用分割出的目标和背景区域的灰度统计量,设计了一个判断是否得到正确分割的准则.理论分析和实验结果表明,对于复杂背景下低对比度、低信噪比的地面目标,不论目标在图像中所占面积大小,利用该方法均可得到正确的分割结果.通过设置阈值运算的灰度取值范围,可大大减少计算量,节省处理时间.
In order to improve the proportion of target detection, a novel adaptive method of automatic threshold selection based on the method of Otsu thresholding is proposed. It takes the gray level statistics of the resultant target and background region as a criterion for discrimination if correct segmentation is obtained. Theoretical analysis shows that correct image segmentation can be obtained for a lowcontrast image with complex background using this method, no matter the proportion of the target is high or low. Moreover, the amount of computation and the processing time can be decreased greatly by setting a graylevel selection threshold. Several experimental results are presented to support the validity of this method.
出处
《北京理工大学学报》
EI
CAS
CSCD
北大核心
2003年第4期521-524,共4页
Transactions of Beijing Institute of Technology
基金
国家部委基金资助项目(039604-1)
关键词
图像处理
图像分割
阈值分割
自适应阈值
红外亚图像
image processing
image segmentation
thresholding segmentation
adaptive thresholding
infrared quiz-image
