Fabry-Perot Spectral Deconvolution with Entropy-weighted Penalization

Miniaturized CMOS hyperspectral cameras utilizing Fabry-Perot Interferometers (FPIs) have emerged as a low-cost solution providing fast-acquisition miniaturized sensors well-suited for both in-field analysis and remote sensing. However, FPIs generate harmonics around each wavelength of interest, hindering the accuracy and reliability of spectral information. This paper proposes a novel scene-dependent spectral correction and calibration method for miniaturized CMOS hyperspectral cameras using FPI technology. Unlike the manufacturer’s scene-independent spectral correction matrix, our approach utilizes deconvolution with Tikhonov regularization weighted by the entropy of the Fabry-Perot harmonics to remove the generated artifacts and restore the original spectra. It adapts to the scene’s unique characteristics, reducing harmonics and improving hyperspectral data quality. The experiments on synthetic data and real images acquired by an FPI sensor demonstrate the superiority of our method in removing harmonic distortions and achieving improved accuracy in spectral calibration.