摘要
提出了有效集成灰度、空间关系和局部标准差信息的新的核密度估计方案,据此设计了一种基于核密度估计的红外目标提取方法,即首先将图像分块,根据块的统计特征获得包含整个目标的约束区域;然后对目标约束区域和相应的背景采样区域进行核密度估计,这里背景采样区域指的是围绕着目标但又不包含目标的图像区域,由目标约束区域向外扩展而形成;最终通过对两种核密度估计对比的阈值判断即能获得所提取的目标.实验验证了所提出的算法简单有效.
A new kernel density estimation scheme which incorporates gray values, spatial relation and local standard deviations information effectively was proposed. With this scheme, an infrared target extraction method based on kernel density estimation was designed. Firstly, the entire image Was divided into blocks and the confined region that contained the entire target was obtained based on the statistical feature of each blocks. Secondly, the kernel density estimations of the confined region and the corresponding background sample region were estimated. Here, the background sample region is a surrounding image region of the target, but it doesnt contain the target. It is enlarged from the confined target region. Finally, the target was extracted with the contrast of two kernel density estimations under a given threshold. The experimental results show that the proposed method is simple and efficient.
出处
《红外与毫米波学报》
SCIE
EI
CAS
CSCD
北大核心
2006年第6期434-438,共5页
Journal of Infrared and Millimeter Waves
基金
国防973项目基金(51323020203-2)
航空科学基金(04F57004)资助项目
关键词
目标提取
统计特征
核密度估计
局部标准差
target extraction
statistical feature
kernel density estimation
local standard deviation
