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基于地质统计学纹理特征的遥感影像分类方法研究

Remote Sensing Image Classification Method Based on Geostatistics Texture

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【作者】 李小涛潘世兵宋小宁

【Author】 LI Xiao-tao1,PAN Shi-bing1,SONG Xiao-ning2(1.Remote Sensing Center of China Institute of Water Resources and Hydropower,Beijing 100044;2.College of Resource and Environment,Graduate University of Chinese Academy of Sciences,Beijing 100049,China)

【机构】 中国水利水电科学研究院遥感中心中国科学院研究生院资源与环境学院

【摘要】 介绍地质统计学的原理与方法,论述了地质统计学应用于遥感影像描述及纹理提取的有效性,并将地质统计学变差函数得到的遥感影像纹理信息与其光谱信息相结合进行遥感影像分类试验,结果表明,辅以地质统计学纹理特征的遥感影像分类方法能够明显提高分类精度。

【Abstract】 The remote sensing image texture information plays an important role in the image classification.Most of traditional classification methods are computational auto-classification based on the image spectral characteristics and ignore the spatial textures of image.Geostatistics,as a science treating the relationship of spatial data,could be applied to image classification.In this paper,the semi-variogram was used to extract textural information of remote sensing image,which was adopted to image classification by means of test.At the same time,the paper discussed the size of computation window,computation direction and computation step according to the practical application.The results proved that the approach combining spectral features and textural measures based on the geostatistics texture to the classification of the remote sensing image may significantly improve the classification accuracy.

【基金】 地理空间信息工程国家测绘局重点实验室经费资助项目(200813);国家自然科学基金项目(40501051、50679086)
  • 【文献出处】 地理与地理信息科学 ,Geography and Geo-Information Science , 编辑部邮箱 ,2009年02期
  • 【分类号】TP751
  • 【被引频次】16
  • 【下载频次】662
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