Compressed ultrafast photography: redefining the limit of passive ultrafast imaging (#4311)
1 UIUC, Urbana, United States of America
A new computational optical imaging method used with a streak camera has enabled two-dimensional ultrafast photography of non-repetitive events at 100 billion frames per second.
Keywords: Compressed imaging, High speed imaging
Continuous High-Rate Photonically-Enabled Compressed Sensing (CHiRP-CS) for High-Speed Optical Imaging Systems (#4312)
M. A. Foster1
1 Johns Hopkins University, Electrical and Computer Engineering, Baltimore, Maryland, United States of America
Real images and most real-world signals are highly compressible and can be accurately represented by relatively few significant coefficients in an appropriate mathematical basis. Traditionally a signal is sampled according to the Nyquist theorem to acquire a raw digital representation and then a compression algorithm is applied, which eliminates as much of the redundancy in the original data as possible. Hence, most of the acquired data is essentially thrown away and, consequently, for most applications in high-speed continuous image acquisition the raw image data bandwidth is far larger than is truly necessary. Compressed sensing is a recent and influential sampling paradigm that advocates a more efficient signal acquisition process by implementing image compression directly in the physical layer. In this talk, I will discuss our recently developed continuous high-rate photonically-enabled compressed sensing (CHiRP-CS) architecture, which allows for high-speed compressive optical imaging beyond the conventional Nyquist limit. In the CHiRP-CS architecture, ultrahigh-rate structured illumination is implemented through high-speed spectral patterning of broadband laser pulses such that every laser pulses acquires a unique pseudorandom spectral amplitude pattern. Compressive measurements are acquired by mixing the structured spectra of the laser pulses with the image signal of interest and capturing the resulting laser pulse energy sequence continuously at a rate of one digital sample per optical pulse. Using this approach, we typically achieve compression rates in the range of 1-10%, which allows for a 10-100x improvement in imaging speed or reduction in image data bandwidth. I will discuss the application of this approach to high-speed flow microscopy for high-throughput cell classification as well as to GHz-rate optical coherence tomography (OCT) for rapid three-dimensional imaging.
Keywords: Compressed Sensing, Optical Microscopy, Optical Coherence Tomography