高光谱影像奇异谱分析特征提取方法:综述与评价  

Singular spectrum analysis method for hyperspectral imagery feature extraction:a review and evaluation

作　　者：孙根云[1,2] 付航 张爱竹 任金昌[3] SUN Genyun;FU Hang;ZHANG Aizhu;REN Jinchang(College of Oceanography and Space Informatics,China University of Petroleum(East China),Qingdao 266580,China;Laboratory for Marine Mineral Resources,Qingdao National Laboratory for Marine Science and Technology,Qingdao 266071,China;The National Subsea Centre,Robert Gordon University,Aberdeen AB107QB,U.K.)

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]海洋国家实验室海洋矿产资源评价与探测技术功能实验室,山东青岛266071 [3]罗伯特戈登大学国家海底中心,苏格兰阿伯丁AB107QB

出　　处：《测绘学报》2023年第7期1148-1163,共16页Acta Geodaetica et Cartographica Sinica

基　　金：国家自然科学基金(42271347,41971292);国家重点研发计划(2019YFE0126700)。

摘　　要：高光谱遥感影像(hyperspectral imagery,HSI)通常包含几十至数百个连续波段,具有图谱合一、光谱连续的特点,能够实现地物的精细分类,被广泛应用农业、林业、城市以及海洋等领域。HSI特征提取是高光谱应用的前提,也是遥感领域的研究热点和前沿课题之一。近年来,奇异谱分析(singular spectrum analysis,SSA)被应用于HSI领域,在光谱特征和空间特征提取方面取得了较好效果,逐渐成为特征提取的一种有效方法。本文首先分析了HSI特征提取的研究进展和存在的问题;其次对SSA方法进行了系统的梳理,分别介绍了光谱域1D-SSA、空间域2D-SSA和光谱-空间组合域SSA 3类方法的作用、效果及优缺点,并在两个公开的HSI数据集和一个高分五号HSI数据上进行了分类效果验证;最后,对SSA特征提取进行了总结,并讨论了未来的研究方向。Hyperspectral remote sensing imagery(HSI)usually contains dozens to hundreds of continuous spectral bands,with the syncretism of spectrum and image,spectral continuity,which can realize fine classification of ground objects and has been widely used in agriculture,forestry,urban and marine areas.The feature extraction of HSI is the premise of hyperspectral applications and has become one of the research hotspots and frontier topics in remote sensing.In recent years,singular spectrum analysis(SSA)has been applied in HSI,achieving superior results in the extraction of spectral and spatial features,and gradually becoming an effective feature extraction method.In this paper,firstly,the research progress and existing problems of HSI feature extraction are analyzed.Secondly,the existing SSA methods are systematically summarized and reviewed.The functions,effects,advantages,and disadvantages of three types of methods,namely,spectral domain 1D-SSA,spatial domain 2D-SSA,and combined spectral-spatial domain SSA,are introduced respectively,and the classification results are verified on two publicly available HSI datasets and one China Gaofen-5 satellite HSI dataset.Finally,the SSA feature extraction is summarized and future research directions are discussed.

关 键 词：高光谱影像 特征提取 奇异谱分析 地物分类 综述 

分 类 号：P237[天文地球—摄影测量与遥感]