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Remote Sensing Technology and Application  2017, Vol. 32 Issue (5): 858-865    DOI: 10.11873/j.issn.1004-0323.2017.5.0858
    
Comparison between Two Spectral Mixture Analysis Methods based on IDL and MATLAB
Xiao Hao1,2,Wang Jie3#br#
(1.Xinjiang Institute of Ecology and Geography,Chinese Academy of Sciences,Urumqi830011,China
2.University of Chinese Academy of Sciences,Beijing100049,China
3.College of Land andResources,China West Normal University,Nanchong 637009,China)
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Abstract  Interactive Data Language (IDL) is a language in the development of application based on multiplatform and object\|oriented,which has significant advantages in data analysis and visualization.The MATLAB is a software with powerful features in the image of processing and programming in complex numerical analysis,which based on matrix calculation.Programming in combining the IDL with MATLAB,meanwhile using the Extended Linear Mixed Model for endmember unmixing in Hyperion images.To verify the results of endmember unmixing,adopted the Fully Constrained Least Squares for comparative analysis.The results showed that:The method of programming in combining the IDL with MATLAB not noly possess the advantages of both but also enhance the efficiency in programming,it is conducive to remote sensing image processing.Meanwhile endmember unmixing results show that:the Extended Linear Mixing Model unmixing has a higher accuracy when the proportion of local category in the image is large.On the contrary,the Fully Constrained Least Squares unmixing has a higher accuracy.
Key words:  Hyperspectral Image      Endmember Variability      Mixed Pixels Unmixing      IDL and MATLAB;Fully Constrained Least Squares;Extended Linear Mixing Model     
Received:  07 August 2016      Published:  02 November 2017
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Xiao Hao,Wang Jie. Comparison between Two Spectral Mixture Analysis Methods based on IDL and MATLAB. Remote Sensing Technology and Application, 2017, 32(5): 858-865.

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http://www.rsta.ac.cn/EN/10.11873/j.issn.1004-0323.2017.5.0858     OR     http://www.rsta.ac.cn/EN/Y2017/V32/I5/858

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