基于IDL和MATLAB混合编程的两种光谱混合分析方法比较

Comparison between Two Spectral Mixture Analysis Methods based on IDL and MATLAB

交互式数据语言IDL是一种跨平台、面向对象的应用程序开发语言,具有强大的数据分析和可视化能力。基于矩阵运算的科学计算软件MATLAB是一种大型数值编程计算和图像处理软件,拥有丰富的工具箱。将IDL和MATLAB进行混合编程,同时采用扩展线性混合模型对Hyperion影像进行端元变化解混。为了验证端元变化解混的结果,采用全约束最小二乘法模型进行对比分析。试验结果表明:IDL和MATLAB混合编程结合两者的优势,有效地提高了代码编写效率;同时,当地物类别所占面积较大时,扩展线性混合模型解混精度比全约束最小二乘法模型高,反之,全约束最小二乘法模型的解混精度高。

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.