Abstract
Compressed sensing-based sampling and scrambling strategies for spectral-domain optical coherence tomography are presented and their performance evaluated. It is shown that the latter can be used for reconstructing both spatially sparse and non-sparse signals.
© 2020 The Author(s)
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