国土资源遥感Issue(3)：1-7,7.DOI:10.6046/gtzyyg.2014.03.01
高光谱图像异常目标检测算法研究与进展
Study and progress of anomaly target detection in hyperspectral imagery
摘要
Abstract
Hyperspectral image is a new kind of remote sensing images with the feature of“combining mapping and spectra into one”,thus better expressing the subtle differences on the surface of the material through the continuous spectral curve. Hyperspectral images have a wide range of applications in such aspects as classification,unmixing and target detection. With the continuous development of hyperspectral remote sensing technology,anomaly target detection has become one of the most active direction of research because it doesn't need a priori information. Many anomaly target detection algorithms have been proposed. Based on data available both in China and abroad, this paper summarized the research situation and new progress in anomaly detection algorithms. The author first expounded the essence of hyperspectral anomaly target detection and used the basic theory and then analyzed and summed up some representative anomaly detection algorithms in such aspects as the ideas of algorithm, key technology,advantages and disadvantages. On such a basis, the author summarized and described the evaluation method of anomaly detection and discussed the future development trend of anomaly target detection algorithm, with the purpose of finding new breakthroughs in the study of the algorithm of hyperspectral anomaly target detection.关键词
高光谱图像/异常目标检测/核函数/支持向量数据描述Key words
hyperspectral image/anomaly target detection/kernel function/support vector data description (SVDD)分类
信息技术与安全科学引用本文复制引用
成宝芝..高光谱图像异常目标检测算法研究与进展[J].国土资源遥感,2014,(3):1-7,7.基金项目
大庆师范学院科学研究基金项目(编号:11ZR09)资助。 （编号:11ZR09）
