US 12,272,033 B2
Snapshot hyperspectral imaging method with de-blurring dispersed images
Xun Cao, Jiangsu (CN); Ye Huang, Jiangsu (CN); Xia Hua, Jiangsu (CN); and Xiaowen Li, Jiangsu (CN)
Assigned to NANJING UNIVERSITY, Jiangsu (CN)
Appl. No. 17/757,367
Filed by NANJING UNIVERSITY, Jiangsu (CN)
PCT Filed Jun. 9, 2020, PCT No. PCT/CN2020/095002
§ 371(c)(1), (2) Date Jun. 15, 2022,
PCT Pub. No. WO2021/135074, PCT Pub. Date Jul. 8, 2021.
Claims priority of application No. 202010006728.0 (CN), filed on Jan. 3, 2020.
Prior Publication US 2023/0021358 A1, Jan. 26, 2023
Int. Cl. G06T 5/73 (2024.01); G01J 3/28 (2006.01); G06T 7/73 (2017.01); G06T 11/00 (2006.01)
CPC G06T 5/73 (2024.01) [G01J 3/2823 (2013.01); G06T 7/74 (2017.01); G06T 11/005 (2013.01); G01J 2003/2826 (2013.01); G01J 2003/283 (2013.01); G06T 2207/10024 (2013.01); G06T 2207/30204 (2013.01)] 7 Claims
OG exemplary drawing
 
1. A snapshot hyperspectral imaging method with deblurring dispersed images using a device capable of dispersing incident light and a sensor configured to capture images dispersed by the device capable of dispersing incident light, wherein in the method comprises the steps of:
S1, selecting a set of reference wavelengths for calibration, rectifying the shifted positions due to dispersion at each reference wavelength, and selecting a center wavelength;
S2, estimating relative dispersion at each reconstructed wavelength with respect to the center wavelength;
S3, generating a dispersion matrix describing the direction of dispersion based on the dispersion results estimated in the S2, and generating a spectral response matrix using a spectral response curve of the sensor;
S4, capturing images blurred with dispersion;
S5, deblurring the dispersed images captured in the S4 using the dispersion matrix and the spectral response matrix generated in the S3 to obtain spectral data spatially aligned in all spectrum; and
S6, projecting the aligned spectral data obtained in the S5 into color space, extracting a foreground image by a threshold method, sampling the dispersed images obtained in the S4 as strong prior constraints for the foreground image, and reconstructing accurate spatial hyperspectral data.