The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Apr. 08, 2025

Filed:

Jun. 09, 2020
Applicant:

Nanjing University, Jiangsu, CN;

Inventors:

Xun Cao, Jiangsu, CN;

Ye Huang, Jiangsu, CN;

Xia Hua, Jiangsu, CN;

Xiaowen Li, Jiangsu, CN;

Assignee:

NANJING UNIVERSITY, Jiangsu, CN;

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06T 5/73 (2024.01); G01J 3/28 (2006.01); G06T 7/73 (2017.01); G06T 11/00 (2006.01);
U.S. Cl.
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);
Abstract

A snapshot hyperspectral imaging method includes the steps of: S, selecting a set of reference wavelengths for calibration, rectifying the shifted positions due to dispersion at each reference wavelength, and selecting a center wavelength; S, estimating relative dispersion at each reconstructed wavelength with respect to the center wavelength; S, generating a dispersion matrix describing the direction of dispersion, and generating a spectral response matrix using a spectral response curve of a sensor; S, capturing images blurred with dispersion; S, deblurring the dispersed images captured in Susing the dispersion matrix and the spectral response matrix generated in Sto obtain spectral data spatially aligned in all spectrums; and S, projecting the aligned spectral data obtained in Sinto color space, extracting a foreground image by a threshold method, sampling the dispersed images obtained in Sas strong prior constraints for the foreground image, and reconstructing accurate spatial hyperspectral data.


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