Title :
Hyperspectral Feature Extraction Based On The Reference Spectral Background Removal Method
Author :
Hengqian Zhao ; Lifu Zhang ; Xia Zhang ; Jia Liu ; Taixia Wu ; Shudong Wang
Author_Institution :
State Key Lab. of Remote Sensing Sci., Inst. of Remote Sensing & Digital Earth, Beijing, China
Abstract :
In spectral analysis, diagnostic absorption features can indicate the existence of specific materials. Absorption parameters such as absorption center, absorption width, and absorption depth can be used in not only identification and quantitative analysis of minerals, but also in retrieval of surface physical properties. Continuum removal (CR) is commonly used to extract absorption features. However, for a band range containing more than one absorption contribution factors, the feature extracted by CR could be a result of comprehensive effect of different factors. In this paper, a new spectral feature extraction method named reference spectral background removal (RSBR) is proposed. Given the reference spectral background, RSBR can eliminate the influence of unwanted contribution factor, and extract the absorption feature of target contribution factor. Using RSBR, the basic absorption feature parameters including the absorption center, absorption width, and absorption depth are extracted. The results are compared with those obtained from the CR. It is shown that RSBR can effectively extract pure absorption features of target material, while more accurate absorption parameters can also be achieved.
Keywords :
feature extraction; geophysical signal processing; hyperspectral imaging; minerals; spectral analysis; RSBR; absorption center; absorption contribution factor; absorption depth; absorption feature extraction; absorption parameter; absorption width; band range; continuum removal; diagnostic absorption feature; hyperspectral feature extraction; mineral identification; mineral quantitative analysis; reference spectral background removal method; spectral analysis; spectral feature extraction method; surface physical property retrieval; Absorption; Earth; Feature extraction; Materials; Minerals; Noise; Remote sensing; Diagnostic absorption feature; hyperspectral remote sensing; mineralogy; reference spectral background removal (RSBR);
Journal_Title :
Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of
DOI :
10.1109/JSTARS.2015.2401052