基于核最小噪声分离变换的高光谱目标探测研究  

Hyperspectral Target Detection Based on Kernel Minimum Noise Separation Transformation

作　　者：张世瑞 樊彦国[1] 张汉德 禹定峰 Zhang Shirui;Fan Yanguo;Zhang Hande;Yu Dingfeng(College of Marine and Spatial Information,China University of Petroleum(East China),Qingdao,Shandong 266580,China;The Sixth Branch of the Coast Guard,Qingdao,Shandong 266012,China;Institute of Oceanographic Instrumentation,Qilu University of Technology,Shandong Academy of Sciences,Qingdao,Shandong 266061,China)

机构地区：[1]中国石油大学(华东)海洋与空间信息学院,山东青岛266580 [2]海警总队第六支队,山东青岛266012 [3]齐鲁工业大学山东省科学院海洋仪器仪表研究所,山东青岛266061

出　　处：《激光与光电子学进展》2021年第12期296-303,共8页Laser & Optoelectronics Progress

基　　金：山东省重点研发计划(2019GHY112017)。

摘　　要：高光谱图像具有非线性的特点,且光谱间具有较强的相关性,利用线性的方法对高光谱数据进行维数变换容易损失一些信息。将核函数引入到最小噪声分离变换(MNF)中,提出了核最小噪声分离变换(KMNF),通过非线性映射将数据映射到高维特征空间,并在高维空间进行最小噪声分离成分的提取。利用高光谱图像较强的谱间相关性和空间邻域相关性,利用前后两个波段和空间邻域加权进行多元线性回归处理,对高光谱数据进行较准确的噪声估计。约束能量最小化(CEM)方法和匹配滤波(MF)方法是高光谱目标探测中较为经典的方法,将KMNF应用到两个经典的目标探测方法中,利用AVIRIS飞机场数据进行高光谱目标探测实验,结果表明,KMNF更能突出目标,提高高光谱目标探测的效果和精度。Hyperspectral images are nonlinear and have a strong inter-spectral correlation.It is easy to lose some information when using a linear method to transform the dimension of hyperspectral data.In this paper,the kernel function is introduced into the minimum noise fraction(MNF),and the kernel minimum noise fraction(KMNF)is proposed.The data is mapped to the high-dimensional feature space through nonlinear mapping,and the minimum noise separation components are extracted in the high-dimensional space.The hyperspectral images have a strong inter-spectral correlation and a spatial neighborhood correlation,and the weights of the two wavebands and the spatial neighborhood are used for multiple linear regression processing to accurately estimate the noise of hyperspectral data.The constrained energy minimization(CEM)method and the matched filter(MF)method are the more classical methods in hyperspectral target detection.The KMNF is applied to two classical target detection methods,and the airfield data from AVIRIS data are used to carry out the hyperspectral target detection experiments.The results show that KMNF can well highlight targets and improve the detection effect and accuracy of hyperspectral targets.

关 键 词：图像处理 核函数 最小噪声分离变换 光谱维 目标探测 

分 类 号：TP751[自动化与计算机技术—检测技术与自动化装置]