光子压缩感知实现了数据高效的时间拉伸光学相干层析成像

Chaitanya K. Mididoddi, Chao Wang
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引用次数: 2

摘要

光子时间拉伸(PTS)实现了实时光谱域光学相干层析成像(OCT)。然而,这种方法会产生以千兆赫赫兹流速率的大量数据流,这需要根据奈奎斯特原理进行捕获。如果OCT干涉图信号在傅里叶域中是稀疏的(对于层数有限的样本总是如此),那么根据压缩感知方法可以以较低的(亚奈奎斯特)采集速率捕获它。本文报道了一种基于光子压缩感知的数据压缩PTS-OCT系统,其压缩率为66%,低采集率为50MHz,每深度剖面测量速度为1.51MHz。提出了一种改进系统的全光随机模式生成方法,完全避免了传统二进制伪随机二进制序列(PRBS)发生器的电子瓶颈。
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Photonic compressive sensing enabled data efficient time stretch optical coherence tomography
Photonic time stretch (PTS) has enabled real time spectral domain optical coherence tomography (OCT). However, this method generates a torrent of massive data at GHz stream rate, which requires capturing as per Nyquist principle. If the OCT interferogram signal is sparse in Fourier domain, which is always true for samples with limited number of layers, it can be captured at lower (sub-Nyquist) acquisition rate as per compressive sensing method. In this work we report a data compressed PTS-OCT system based on photonic compressive sensing with 66% compression with low acquisition rate of 50MHz and measurement speed of 1.51MHz per depth profile. A new method has also been proposed to improve the system with all-optical random pattern generation, which completely avoids electronic bottleneck in traditional binary pseudorandom binary sequence (PRBS) generators.
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