Several automated image background removal schemes for use with line-imaging Raman spectroscopy are compared. An image of electrodeposited beta -CuSCN produced by line-imaging Raman spectroscopy (one spectral
dimension, one spatial dimension) is background corrected by the adapted Pearson's method (APM), a Fourier filtering method, and the mathematical morphology method of the rolling cylinder. APM is shown
to perform best overall, but is the most computationally taxing because of the iterative nature of the algorithm. The effects of the APM parameters are discussed.
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