Spectral unmixing and image classification supported by spatial knowledge

Bing Zhang; Xia Zhang; Liangyun Liu; Lanfen Zheng; Qingxi Tong

doi:10.1117/12.467408

16 June 2003 Spectral unmixing and image classification supported by spatial knowledge

Bing Zhang, Xia Zhang, Liangyun Liu, Lanfen Zheng, Qingxi Tong

Proceedings Volume 4897, Multispectral and Hyperspectral Remote Sensing Instruments and Applications; (2003) https://doi.org/10.1117/12.467408
Event: Third International Asia-Pacific Environmental Remote Sensing Remote Sensing of the Atmosphere, Ocean, Environment, and Space, 2002, Hangzhou, China

Abstract

Usually the spectral unmixing and endmember extraction were based on the spectral statistics algorithm. In this paper, spatial knowledge, such as field patch information, was involved in the pure pixel selecting. In this way, endmember extraction was not only carried out in spectral space but also considering the spatial location of pixels. In addition, these known background information can also improve the accuracy of image classification, and also can be used to intellectually separate pixels and evaluate each sub-pixels different attributes.

Citation Download Citation

Bing Zhang, Xia Zhang, Liangyun Liu, Lanfen Zheng, and Qingxi Tong "Spectral unmixing and image classification supported by spatial knowledge", Proc. SPIE 4897, Multispectral and Hyperspectral Remote Sensing Instruments and Applications, (16 June 2003); https://doi.org/10.1117/12.467408

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