Nanjing University

Xiaowen Li

Xun Cao

Xia Hua

Ye Huang

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.

Snapshot hyperspectral imaging method with de-blurring dispersed images

A method for removing periodic noise from a reconstructed light field image includes the steps of: acquiring a light field image of a sample; acquiring an optical center position map without the sample; calibrating the imaging centers of the microlenses and performing reconstruction on the light field image; transforming a reconstructed light field image to the frequency domain and generating an image frequency spectrum; preprocessing the image frequency spectrum; generating a low-pass filter; multiplying the low-pass filter with the preprocessed image frequency spectrum, and then setting the frequency spectrum value of the low-frequency component to zero; performing binarization on the reconstructed light field image frequency spectrum to obtain an image mask; removing the high-frequency periodic noise component from the original frequency spectrum of the reconstructed light field image; and transforming the filtered reconstructed light field image frequency spectrum back to the spatial domain to obtain the reconstructed light field image.

Growing community of inventors

Jiangsu, China

Xiaowen Li