Infrared and Laser Engineering, Volume. 54, Issue 3, 20240392(2025)
Denoising method of continuous light spatial heterodyne interferogram based on deep convolutional neural network
[1] [1] HARLER J M. Spatial Heterodyne Spectroscopy: Interferometric Perfmance at any Wavelength without Scanning[M]. Madison: The University of WisconsinMadison, 1991.
[15] [15] SHINDE P P, SHAH S. A review of machine learning deep learning applications[C]2018 Fourth International Conference on Computing Communication Control Automation (ICCUBEA). IEEE, 2018: 16.
[17] [17] PARKHI O, VEDALDI A, ZISSERMAN A. Deep face recognition[C]BMVC 2015Proceedings of the British Machine Vision Conference 2015. British Machine Vision Association, 2015.
[19] [19] HUANG J, LI J, GONG Y. An analysis of convolutional neural wks f speech recognition[C]2015 IEEE International Conference on Acoustics, Speech Signal Processing (ICASSP). IEEE, 2015: 49894993.
[23] [23] ANWAR S, BARNES N. Real image denoising with feature attention[C]Proceedings of the IEEECVF International Conference on Computer Vision. 2019: 31553164.
[27] [27] GU S, ZHANG L, ZUO W, et al. Weighted nuclear nm minimization with application to image denoising[C]Proceedings of the IEEE Conference on Computer Vision Pattern Recognition. 2014: 28622869.
[29] [29] GU S, ZUO W, XIE Q, et al. Convolutional sparse coding f image superresolution [C]Proceedings of the IEEE International Conference on Computer Vision. 2015: 18231831.
Get Citation
Copy Citation Text
Wei LUO, Song YE, Wei XIONG, Ziyang ZHANG, Xinqiang WANG, Shu LI, Fangyuan WANG. Denoising method of continuous light spatial heterodyne interferogram based on deep convolutional neural network[J]. Infrared and Laser Engineering, 2025, 54(3): 20240392
Category: Optical imaging, display and information processing
Received: Sep. 10, 2024
Accepted: --
Published Online: Apr. 8, 2025
The Author Email: