AI Article Synopsis
- Based on empirical mode decomposition (EMD), the study implements background removal and de-noising for data from a polarization interference imaging interferometer (PIIS), showing effective results through numerical simulations.
- It confirms that most noise exists in the first intrinsic mode function, establishes EMD de-noising parameters, and compares these methods with wavelet and Fourier transform approaches using metrics like SNR, spectral resolution, and peak value.
- The methods effectively suppress Gaussian and Poisson noise, achieving better de-noising efficiency for Gaussian noise. Ultimately, they successfully yield background-free interferograms and noise-free spectra.
Article Abstract
Based on empirical mode decomposition (EMD), the background removal and de-noising procedures of the data taken by polarization interference imaging interferometer (PIIS) are implemented. Through numerical simulation, it is discovered that the data processing methods are effective. The assumption that the noise mostly exists in the first intrinsic mode function is verified, and the parameters in the EMD thresholding de-noising methods is determined. In comparison, the wavelet and windowed Fourier transform based thresholding de-noising methods are introduced. The de-noised results are evaluated by the SNR, spectral resolution and peak value of the de-noised spectrums. All the methods are used to suppress the effect from the Gaussian and Poisson noise. The de-noising efficiency is higher for the spectrum contaminated by Gaussian noise. The interferogram obtained by the PIIS is processed by the proposed methods. Both the interferogram without background and noise free spectrum are obtained effectively. The adaptive and robust EMD based methods are effective to the background removal and de-noising in PIIS.
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| http://dx.doi.org/10.1364/OE.21.002592 | DOI Listing |
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