Laser & Optoelectronics Progress, Volume. 60, Issue 10, 1030002(2023)
Filtering Hyperspectral Imaging Technology Based on Deep Learning
Fig. 1. Spectral imaging model. (a) Schematic of principle; (b) schematic of network
Fig. 4. Comparison of the spectral reconstruction performance of the optimized model with two structural filter schemes. (a) RGB image, tf MRAE and nl MRAE images, tf MRAE hist and nl MRAE hist images; (b) reconstructed irradiance of some pixels in sample No. 3
Fig. 5. Comparison of the optimized filter's spectral response function. (a) Thin film interference filter scheme; (b) no-limited structure filter scheme
Fig. 6. Impact of various array sizes on the spectral imaging performance of no-limited structure filters. (a) RGB image, tf MRAE and nl MRAE images, tf MRAE hist and nl MRAE hist images; (b) reconstructed irradiance of some pixels in sample No. 3
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Xueli Lin, Zilin Wang, Yanxia Zou, Hao Liu, Ran Hao, Shangzhong Jin. Filtering Hyperspectral Imaging Technology Based on Deep Learning[J]. Laser & Optoelectronics Progress, 2023, 60(10): 1030002
Category: Spectroscopy
Received: Mar. 14, 2022
Accepted: Apr. 19, 2022
Published Online: May. 17, 2023
The Author Email: Shangzhong Jin (jinsz@cjlu.edu.cn)