Spatial–spectral preprocessing for spectral unmixing. Issue 4 (16th February 2019)

• Record Type: Journal Article
• Authors: Yan, Yang; Hua, Wenshen; Liu, Xun; Cui, Zihao; Diao, Dongmei
• Is Part Of: International journal of remote sensing. Volume 40:Issue 4(2019)
• Page Start: 1357
• Page End: 1373
• Publication Date: 2019-02-16
• Subjects: Remote sensing -- Periodicals; Télédétection -- Périodiques; 621.3678
• DOI: 10.1080/01431161.2018.1524590
• Languages: English
• ISSNs: 0143-1161

Abstract

ABSTRACT: Most techniques available in the endmember extraction rely on exploiting the spectral information of the data alone. In this paper, we improve the utilization of data information by dividing a pixel into four subpixels which are redefined by the scalar factor related to the spatial–spectral similarity. The spatial information is integrated into the spectral information in a certain spatial neighbourhood domain, which can make extracted endmembers more precisely, because the effect of noise and outliers can be suppressed with preprocessing (PP). Meanwhile, the accuracy of spectral unmixing will be improved without modification to the conventional methods applied to spectral-based endmember extraction. Experimental results with both synthetic and real hyperspectral images demonstrate the unmixing accuracy is better than that without PP.