A study on denoising with deep convolutional neural networks in spatial heterodyne spectroscopy-Reference-Cited by-同舟云学术

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A study on denoising with deep convolutional neural networks in spatial heterodyne spectroscopy

Published:2024-04 Issue: Volume:316 Page:108918
ISSN:0022-4073
Container-title:Journal of Quantitative Spectroscopy and Radiative Transfer
language:en
Short-container-title:Journal of Quantitative Spectroscopy and Radiative Transfer

Author:

Luo Wei,Ye Song,Zhang Ziyang,Liu Shuang,Xiong Wei,Wang Xinqiang,Li Shu,Wang Fangyuan,Dong Baijun

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Publisher

Elsevier BV

Reference39 articles.

1. Spatial heterodyne spectroscopy: interferometric performance at any wavelength without scanning;Harlander,1991

2. Spatial heterodyne spectroscopy for the exploration of diffuse interstellar emission lines at far-ultraviolet wavelengths;Harlander;Astrophys J 1,1992

3. Shimmer: a spatial heterodyne spectrometer for remote sensing of Earth'middle atmosphere;Harlander;Appl Opt,2002

4. Spatial Heterodyne Observations of Water (SHOW) vapour in the upper troposphere and lower stratosphere from a high altitude aircraft: modelling and sensitivity analysis;Langille;J Quant Spectrosc Radiat Transf,2018

5. Study on near-infrared spatial heterodyne spectrometer and detection of water vapor;Xiong;Acta Opt Sin,2010

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