导　　师： 罗传文

学科专业： 090704

授予学位： 硕士

作　　者： ;

机构地区： 东北林业大学

摘　　要： 本文主要围绕hyperion高光谱遥感数据在混合像元分解技术中的应用这个中心展开，比较了基于多光谱的传统分类方法和适用于高光谱的混合像元分解分类方法的差异。 由于传感器空间分辨率的限制以及地物的复杂多样性，混合像元普遍存在于遥感影像中，它涉及成像机理、特征提取、应用技术等一系列不能回避的问题；同时，混合像元分解也是遥感图像分类的重要途径之一。混合像元分解存在两大难点：(1)终端端元的确定与提取，(2)混合分解模型的求解。 首先针对hyperion高光谱遥感数据的特点，对hyperion图像进行了必要的预处理，为图像的进一步分析和实际应用提供了保障。在混合像元分解模型确定的前提下，端元组分选择的优劣直接影响混合像元分解的精度。针对高光谱遥感分类过程中终端端元光谱的选择问题，首先研究分析了高光谱分类过程中常用的终端端元光谱的来源和选择方法，在原有的两种终端端元光谱提取方法上，提出了改进的ppi提取方法，并利用sam光谱角制图法，结合具体的高光谱遥感数据验证该方法的有效性。针对高光谱遥感分类中混合像元的分解问题，探讨混合像元的概念和几种常用的混合像元分解模型，并对常用的线性分解模型给出了详细的求解过程：无约束条件线性分解和有约束条件线性分解。然后结合具体的高光谱遥感图像数据，对比分析基于多光谱的传统分类方法和适用于高光谱的混合像元分解分类方法的优缺点，并进一步分析比较了有无约束条件的线性分解模型，验证混合像元分解应用于高光谱遥感分类的实用性和有效性。 This paper focuses on application of Hyperion hyperspectral remote sensing data in mixed pixels unmixing technology, compares the traditional classification method and hyperspectral classification method of mixed pixels unmixing.It is a well-known fact that pixels in remote sensing image are typically mixed pixels due to both the limited spatial resolution of sensors and the heterogeneous surfaces of ground covers. Mixed pixels are a major source of inconvenience in conventional classification. There are two difficult points about mixed pixels unmixing: /(1/)Determine and pick-up the end members/(2/)solve the modle of mixed pixels unmixing.For the characteristics of Hyperion hyperspectral remote sensing data, at first the paper pretreated Hyperion image and provide the guarantee for further analytical and actual application image. With the premise of assuring pixel immixing model, wether good or bad it is, the choice of endmembers directly influence accuracy of pixel unmixing.For the choice problem of terminal component endmembers in the classification process of hyperspectral remote sensing, this paper study and analyze the source and choice method of terminal component endmembers spectrum. With two kinds original methods of withdraw terminal component endmember,this paper raise improvement PPI method of withdraw and make use of the combineness usefulness of the method of SAM to testify practicability and validity of PPI.For the unmixing of mixed pixels,the paper describes unrestricted linear mixing method and restricted linear mixing method of unmixing model,and give its unmixing methods available. With the hyperspectral remote sensing,the paper compares traditional classification with unmixing of mixed pixels ,compares unrestricted linear mixing method and restricted linear mixing method of unmixing model, and testify practicability and validity of unmixing of mixed pixels in hyperspectral classification.

关 键 词： 高光谱遥感数据 终端端元 混合像元分解 分解模型

分 类 号： [S771.8 TP75]

领　　域： [农业科学] [农业科学] [自动化与计算机技术] [自动化与计算机技术]