I've produced several thousand Raman spectra using hyperspectral imaging techniques. These suffer from significant fluorescent interference which produces a curved, sloped baseline. Using Matlab, I have attempted several baseline subtraction techniques but I can't say quantitatively which is performing best - beyond a visual inspection I'm not sure how to compare them.
Is there any quantitative way of assessing the performance of a baseline subtraction? Or is visual inspection really the best we can do?
Thanks for taking the time to consider this.
Edit: I've added an example spectrum along with one with a corrected baseline.
Thank you for your suggestions as regards methods for baseline correction, however, I have already used several different methods successfully. My intention was to discover if there was a way of measuring the performance of various techniques in order to asses which is the most effective.
Thanks again for your consideration.
Edit 2: I just wish to clarify that I am not looking for methods for baseline correction. I have used several which have given me varying results - these include polynomial fitting, piece wise fitting, ModPoly, subtraction of iteratively smoothed savitzky-golay baselines, and WPLS. What I'm looking for is a way to quantify their performance, is there any metric that can be used to do this?