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基于蜂群优化投影寻踪的高光谱小目标检测

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  • 维普
为了进一步提高高光谱遥感图像小目标无监督检测方法的运算速度，并降低其虚警率，提出了一种基于改进蜂群优化投影寻踪与 K 最近邻的检测方法。首先，采用核主成分分析法对原始高光谱遥感图像进行降维；然后，提出以邻域像元联合定义峰度与偏度的方法，并将两者结合作为投影指标，再以改进后的蜂群算法作为寻优方法，使用投影寻踪从高光谱图像中逐层获取投影图像，再根据其直方图提取小目标；最后，利用线性判别分析进一步提取像元特征，并结合加权 K 最近邻方法对小目标的检测结果进行提纯。大量实验结果表明，与 RX 方法、独立分量分析法、混沌粒子群优化投影寻踪法相比，本文方法不但可以更精确地检测出高光谱遥感图像中的小目标，而且具有更快的运算速度。
Detection of hyperspectral small targets based on projection pursuit optimized by bee colony
In order to further improve the operation speed and reduce the false alarm rate of the unsupervised detection method for small targets in hyperspectral remote sensing images,a detection method based on the projection pursuit (PP)optimized by improved artificial bee colony (ABC)optimization algorithm and K-nearest neighbor (KNN)is proposed in this paper.Firstly,the kernel principal component analysis (KPCA)method is adopted to perform the dimension reduction of the original hyperspectral remote sensing images. Then,the method jointly defining the kurtosis and skewness according to the neighborhood pixels is proposed,the combination of the kurtosis and skewness is taken as the projection index.The improved artificial bee colony algorithm is taken as the optimization algorithm.The projection pursuit is used to obtain the projection images layer by layer from the low dimensional hyperspectral remote sensing images,and the small targets are extracted according to the histogram of these projection images.Finally,the linear discriminant analysis (LDA)is used to extract the features of the pixels,and the weighted K-nearest neighbor method is used to purify the preliminary detection results of the small targets.A large number of experiment results show that compared with the RX method, independent component analysis (ICA)method and the projection pursuit method based on chaotic particle swarm optimization (CPSO), the proposed method not only can detect the small targets in hyperspectral remote sensing image accurately,but also has faster operation speed.

remote sensinghyperspectral imagesmall target detectionimproved bee colony optimization algorithmprojection pursuitK-nearest neighbor

吴一全、周杨、龙云淋

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南京航空航天大学 电子信息工程学院 南京 211106

中国科学院西安光学精密机械研究所 中科院光谱成像技术重点实验室 西安 710119

遥感 高光谱图像 小目标检测 改进的蜂群优化算法 投影寻踪 K 最近邻

国家自然科学基金中国科学院光谱成像重点实验室开放基金江苏高校优势学科建设工程项目

61573183LSIT201401

2016

仪器仪表学报
中国仪器仪表学会

仪器仪表学报

CSTPCDCSCD北大核心EI
影响因子：2.372
ISSN：0254-3087
年,卷(期)：2016.37(6)
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