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. Author manuscript; available in PMC: 2023 Jan 3.
Published in final edited form as: Opt Express. 2020 Jul 6;28(14):20422–20437. doi: 10.1364/OE.397606

Fig. 1.

Fig. 1.

(a) Workflow for the conventional denoising, KK, PEC, and SEC, where m is the total number of spatial pixels (“flattened") and n is the number of frequency channels. (b) Workflow for the fKK-EC where the processing steps are performed on basis vectors rather than the underlying spectra. (c) Workflow for the ML:fKK-EC in which only the training data is processed via the fKK-EC and regression is used to transform new data.