High-Throughput Photonic Time-Stretch Optical Coherence Tomography with Data Compression

Photonic time stretch enables real-time high-throughput optical coherence tomography (OCT), but with massive data volume being a real challenge. In this paper, data compression in high-throughput optical time-stretch OCT has been explored and experimentally demonstrated. This is made possible by exploiting the spectral sparsity of an encoded optical pulse spectrum using a compressive sensing approach. Both randomization and integration have been implemented in the optical domain avoiding electronic bottleneck. A data compression ratio of 66% has been achieved in high-throughput OCT measurements with 1.51-MHz axial scan rate using greatly reduced data sampling rate of 50 MS/s. Potential to improve compression ratio has been exploited. In addition, using a dual pulse integration method, capability of improving frequency measurement resolution in the proposed system has been demonstrated. A number of optimization algorithms for the reconstruction of the frequency-domain OCT signals have been compared in terms of reconstruction accuracy and efficiency. Our results show that the l(1) magic implementation of the primal-dual interior point method offers the best compromise between accuracy and reconstruction time of the time-stretch OCT signal tested.