Title :
A Novel Approach Based on Fisher Discriminant Null Space for Decomposition of Mixed Pixels in Hyperspectral Imagery
Author :
Jin, Jing ; Bin Wang ; Zhang, Liming
Author_Institution :
Electron. Eng. Dept., Fudan Univ., Shanghai, China
Abstract :
Traditional spectral mixture analysis assumes that each endmember must have a constant spectral signature. However, endmember spectral variability always exists in practical situations, which results in reducing the accuracy of the decomposition of mixed pixels. In order to solve this problem, this letter proposes a new method based on Fisher discriminant null space (FDNS) for decomposition of mixed pixels in hyperspectral imagery. The FDNS searches a linear transformation of the spectra, which makes those endmember spectra to have no variability inside each endmember group but large differences among different endmember groups. Therefore, the negative impact caused by endmember spectral variability on unmixing accuracy can be decreased to a large extent by using the transformed spectra. Experimental results of both simulated and real hyperspectral images demonstrate that the proposed algorithm has a high accuracy for the decomposition of mixed pixels in hyperspectral imagery.
Keywords :
image segmentation; matrix algebra; remote sensing; Fisher discriminant null space; hyperspectral imagery; linear transformation; mixed pixel decomposition; spectral mixture analysis; spectral variability; Electromagnetic scattering; Electromagnetic spectrum; Focusing; Hyperspectral imaging; Hyperspectral sensors; Image analysis; Null space; Pixel; Remote sensing; Spectral analysis; Decomposition of mixed pixels; Fisher discriminant null space (FDNS); endmember spectral variability; hyperspectral imagery; hyperspectral unmixing;
Journal_Title :
Geoscience and Remote Sensing Letters, IEEE
DOI :
10.1109/LGRS.2010.2046134