Compact speckle spectrometer based on CNN-LSTM denoising
We propose a compact speckle spectrometer that utilizes micro-nanostructures processed by femtosecond lasers on sapphire surfaces as scattering media. The spectral resolution is 0.5 nm, and the entire system is compact and stable. At the same time, the convolutional long short-term memory network (CNN-LSTM) was introduced into the denoising algorithm. Compared with traditional reconstruction algorithms, this method not only ensures rapid spectral reconstruction but also offers better reconstruction accuracy. It can effectively reduce the reconstruction error caused by the reduction of speckle autocorrelation caused by environmental noise and prolong the stability time of the system.
Authors
- Yunlong Xu
- Shouhuan Zhou (ORCID: https://orcid.org/0000-0002-8487-0913)
- Guoliang Deng (ORCID: https://orcid.org/0000-0003-3684-3408)
- Hong Zhao (ORCID: https://orcid.org/0000-0002-7820-0171)
- Rui Cai (ORCID: https://orcid.org/0000-0003-2342-5194)
- Jie Wu (ORCID: https://orcid.org/0000-0003-1069-9372)
- Hong Zhang (ORCID: https://orcid.org/0009-0002-4319-5488)
- Hao Zhou (ORCID: https://orcid.org/0009-0007-5404-1333)
Publication Details
- Journal
- Optics Letters
- Published
- 2024-11-04
- DOI
- https://doi.org/10.1364/ol.541088
- Citations
- 3
- Primary Topic
- Photonic and Optical Devices
- Type
- article
- Field-Weighted Citation Impact
- 0.63
Funders
- National Key Research and Development Program of China