Sampling and Scrambling in Compressive Sensing Based Spectral Domain Optical Coherence Tomography

摘要

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.