[Quantitative evaluation of soil hyperspectra denoising with different filters].
Identifieur interne : 000265 ( Ncbi/Curation ); précédent : 000264; suivant : 000266[Quantitative evaluation of soil hyperspectra denoising with different filters].
Auteurs : Ming-Xiang Huang [République populaire de Chine] ; Ke Wang ; Zhou Shi ; Jian-Hua Gong ; Hong-Yi Li ; Jie-Liang ChenSource :
- Guang pu xue yu guang pu fen xi = Guang pu [ 1000-0593 ] ; 2009.
Abstract
The noise distribution of soil hyperspectra measured by ASD FieldSpec Pro FR was described, and then the quantitative evaluation of spectral denoising with six filters was compared. From the interpretation of soil hyperspectra, the continuum removed, first-order differential and high frequency curves, the UV/VNIR (350-1 050 nm) exhibit hardly noise except the coverage of 40 nm in the beginning 350 nm. However, the SWIR (1 000-2 500 nm) shows different noise distribution. Especially, the latter half of SWIR 2(1 800-2 500 nm) showed more noise, and the intersection spectrum of three spectrometers has more noise than the neighbor spectrum. Six filters were chosen for spectral denoising. The smoothing indexes (SI), horizontal feature reservation index (HFRI) and vertical feature reservation index (VFRI) were designed for evaluating the denoising performance of these filters. The comparison of their indexes shows that WD and MA filters are the optimal choice to filter the noise, in terms of balancing the contradiction between the smoothing and feature reservation ability. Furthermore the first-order differential data of 66 denoising soil spectra by 6 filters were respectively used as the input of the same PLSR model to predict the sand content. The different prediction accuracies caused by the different filters show that compared to the feature reservation ability, the filter's smoothing ability is the principal factor to influence the accuracy. The study can benefit the spectral preprocessing and analyzing, and also provide the scientific foundation for the related spectroscopy applications.
PubMed: 19455808
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From the interpretation of soil hyperspectra, the continuum removed, first-order differential and high frequency curves, the UV/VNIR (350-1 050 nm) exhibit hardly noise except the coverage of 40 nm in the beginning 350 nm. However, the SWIR (1 000-2 500 nm) shows different noise distribution. Especially, the latter half of SWIR 2(1 800-2 500 nm) showed more noise, and the intersection spectrum of three spectrometers has more noise than the neighbor spectrum. Six filters were chosen for spectral denoising. The smoothing indexes (SI), horizontal feature reservation index (HFRI) and vertical feature reservation index (VFRI) were designed for evaluating the denoising performance of these filters. The comparison of their indexes shows that WD and MA filters are the optimal choice to filter the noise, in terms of balancing the contradiction between the smoothing and feature reservation ability. Furthermore the first-order differential data of 66 denoising soil spectra by 6 filters were respectively used as the input of the same PLSR model to predict the sand content. The different prediction accuracies caused by the different filters show that compared to the feature reservation ability, the filter's smoothing ability is the principal factor to influence the accuracy. The study can benefit the spectral preprocessing and analyzing, and also provide the scientific foundation for the related spectroscopy applications.</div></front></TEI></record>Pour manipuler ce document sous Unix (Dilib)
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