Noise reduction in the spectral domain of hyperspectral images using denoising autoencoder methods

Denoising of spectra has been a great challenge in hyperspectral image analysis. Near-infrared hyperspectral images of milk powder, rice flour and soybean flour were acquired and denoising in the spectral domain were studied. Noise free spectra and noises were simulated based on sample pixel-wise sp...

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Veröffentlicht in:	Chemometrics and intelligent laboratory systems Jg. 203; S. 104063
Hauptverfasser:	Zhang, Chu, Zhou, Lei, Zhao, Yiying, Zhu, Susu, Liu, Fei, He, Yong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier B.V 15.08.2020
Schlagworte:	Denoising autoencoder Empirical mode decomposition Hyperspectral image Noise reduction Spectra simulation Wavelet transform Denoising autoencoder Empirical mode decomposition Wavelet transform Hyperspectral image Spectra simulation Noise reduction
ISSN:	0169-7439, 1873-3239
Online-Zugang:	Volltext
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