Alternate Title

Spectrum Denoising of Raman Spectroscopy Signals


Raman spectroscopy measurements are affected by various types of spurious signals or noise. These spurious signals in the detection system are mainly produced by cosmic rays, read-out noise and thermal noise. Because of the very different nature of the various noise signals, the procedure to estimate a desired materials spectral response from the measured signal is generally divided into two sequential stages. The first stage removes the impulsive noise caused by cosmic rays, and the second attempts to remove the rest of the noise. In this work, the algorithm for removing the impulsive noise is based on a system which uses both a median filter and classic pattern recognition techniques. The algorithm not only removes the impulse, but replaces the missing values with the best estimates including system noise. In addition, spectrum denoising to minimize the loss of information is studied. The implemented algorithms are tested with synthetic and real spectrums, real spectrums are from Raman Imaging of biological materials which were provided by the research group led by professor Max Diem at Northeastern University. The algorithms are useful for all software tools that analyze Raman spectroscopy data.


Poster presented at the 2006 Thrust R2C Multi Spectral Discrimination Methods Conference


Denoising, software, cosmic rays, noise

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Raman spectroscopy




Bernard M. Gordon Center for Subsurface Sensing and Imaging Systems (Gordon-CenSSIS)

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Bernard M. Gordon Center for Subsurface Sensing and Imaging Systems (Gordon-CenSSIS)

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