Photon Doppler velocimetry (PDV) is a widely used diagnostic for measuring extreme surface velocities. Due to limited electrical bandwidth, conventional PDV systems suffer from limited velocity dynamic range when measuring extreme phenomena in shock physics. Time lens PDV (TL-PDV) overcomes these limitations by temporally magnifying the Doppler shifted beat frequencies allowing for recording with lower bandwidth electronics. Here we experimentally demonstrate TL-PDV and show a 74 km/s velocity range using only 12.5 GHz electrical bandwidth and a temporal magnification factor of 7.6. Furthermore, we validate this system by measuring Laser-Driven Micro-Flyers (LDMF) traveling at approximately 1 km/s.
KEYWORDS: Optical testing, Data compression, Data acquisition, Compressed sensing, Signal processing, Image compression, Image processing, Algorithms, Optical signal processing, Imaging systems
High-speed optical measurement systems are wholly constrained by the number of measurements that can be acquired in a limited amount of time. Unfortunately, most of these painstakingly acquired measurements are wasted collecting much more data than is required to accurately determine a given signal of interest. Specifically, real-world signals (e.g. images) are highly compressible and can be accurately represented by relatively few significant coefficients in an appropriate mathematical basis. Traditionally a signal is sampled in the physical domain 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 measurement the raw data bandwidth is far larger than is truly necessary. In this talk, we will discuss our recent research in applying optical signal processing and compressed sensing to enhance performance in such high-speed measurement-limited applications. 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. Specifically, we will discuss our research into constructing compressed sensing based optical hardware systems for high-throughput microscopy, optical coherence tomography, LIDAR, and hyperspectral imaging.
Multiphoton microscopes are of paramount importance in capturing neural activity with cellular resolution. However, the imaging speed and field-of-view of traditional two-photon microscopes is limited by raster scanning technologies. Temporally-focused two-photon (TFTP) microscopy is a wide-field scan-free approach to increase the speed of two-photon microscopy. In conventional TFTP microscopy, wide-field depth sectioning is obtained by compressing a spatially pre-chirped pulse at the focal plane of the objective. Unfortunately, the greater imaging speed of TFTP microscopes comes at the expense of poor imaging depth in tissue due to scattering of the short-wavelength fluorescence photons en-route to the imaging camera. Here we demonstrate a compressive high-speed two-photon microscope based on wide-field temporally-focused structured illumination, which eliminates the loss of image contrast from scattering of the fluorescence signal by leveraging a single-pixel detector. Specifically, we illuminate the sample with a rapid sequence of randomly structured temporally-focused wide-field illumination pulses and integrate the net two-photon fluorescence response on a single photomultiplier tube (PMT). Notably, the longer wavelength structured illumination is significantly less susceptible to scattering and the use of integrated measurements on a single PMT provides immunity to fluorescence scattering since these measurements are solely concerned with the net fluorescence. Furthermore, our approach provides greater speed than point scanning two-photon microscopes through the use of wide-field illumination and compressive image acquisition. Experimentally we demonstrate this system operating over a 200×250-μm field-of-view and at a compression rate of 10%, which provides an order of magnitude increase in speed over a comparable point scanning architecture.
Imaging systems can become measurement limited under various conditions resulting in strict limits to the amount of acquired image information. For example, a high-speed imager is limited in the number of measurements that can be acquired per second. Similarly, an ultra-small imager such as a micro-endoscope is limited by the number of measurements that can be acquired in a given cross-sectional area. In this talk, we will discuss our recent research in applying optical signal processing and computational imaging to enhance imaging performance in measurement-limited applications. Specifically, we will discuss our research into high-throughput flow microscopes for imaging flow cytometry and ultra-small fiber imagers for minimally-invasive micro-endoscopy.
Photonic time-stretch microscopy (TSM) provides an ideal platform for high-throughput imaging flow cytometry, affording extremely high shutter speeds and frame rates with high sensitivity. In order to resolve weakly scattering cells in biofluid and solve the issue of signal-to-noise in cell labeling specificity of biomarkers in imaging flow cytometry, several quantitative phase (QP) techniques have recently been adapted to TSM. However, these techniques have relied primarily on sensitive free-space optical configurations to generate full electric field measurements. The present work draws from the field of ultrashort pulse characterization to leverage the coherence of the ultrashort optical pulses integral to all TSM systems in order to do self-referenced single-shot quantitative phase imaging in a TSM system. Self-referencing is achieved via spectral shearing interferometry in an exceptionally stable and straightforward Sagnac loop incorporating an electro-optic phase modulator and polarization-maintaining fiber that produce sheared and unsheared copies of the pulse train with an inter-pulse delay determined by polarization mode dispersion. The spectral interferogram then yields a squared amplitude and a phase derivative image that can be integrated for conventional phase. We apply this spectral shearing contrast microscope to acquire QP images on a high-speed flow microscope at 90-MHz line rates with <400 pixels per line. We also consider the extension of this technique to compressed sensing (CS) acquisition by intensity modulating the interference spectra with pseudorandom binary waveforms to reconstruct the images from a highly sub-Nyquist number of random inner products, providing a path to even higher operating rates and reduced data storage requirements.
The process of multiple scattering has inherent characteristics that are attractive for high-speed imaging with high spatial resolution and a wide field-of-view. A coherent source passing through a multiple-scattering medium naturally generates speckle patterns with diffraction-limited features over an arbitrarily large field-of-view. In addition, the process of multiple scattering is deterministic allowing a given speckle pattern to be reliably reproduced with identical illumination conditions. Here, by exploiting wavelength dependent multiple scattering and compressed sensing, we develop a high-speed 2D time-stretch microscope. Highly chirped pulses from a 90-MHz mode-locked laser are sent through a 2D grating and a ground-glass diffuser to produce 2D speckle patterns that rapidly evolve with the instantaneous frequency of the chirped pulse. To image a scene, we first characterize the high-speed evolution of the generated speckle patterns. Subsequently we project the patterns onto the microscopic region of interest and collect the total light from the scene using a single high-speed photodetector. Thus the wavelength dependent speckle patterns serve as high-speed pseudorandom structured illumination of the scene. An image sequence is then recovered using the time-dependent signal received by the photodetector, the known speckle pattern evolution, and compressed sensing algorithms. Notably, the use of compressed sensing allows for reconstruction of a time-dependent scene using a highly sub-Nyquist number of measurements, which both increases the speed of the imager and reduces the amount of data that must be collected and stored. We will discuss our experimental demonstration of this approach and the theoretical limits on imaging speed.
High-speed continuous imaging systems are constrained by analog-to-digital conversion, storage, and transmission. However, real video signals of objects such as microscopic cells and particles require only a few percent or less of the full video bandwidth for high fidelity representation by modern compression algorithms. Compressed Sensing (CS) is a recent influential paradigm in signal processing that builds real-time compression into the acquisition step by computing inner products between the signal of interest and known random waveforms and then applying a nonlinear reconstruction algorithm. Here, we extend the continuous high-rate photonically-enabled compressed sensing (CHiRP-CS) framework to acquire motion contrast video of microscopic flowing objects. We employ chirp processing in optical fiber and high-speed electro-optic modulation to produce ultrashort pulses each with a unique pseudorandom binary sequence (PRBS) spectral pattern with 325 features per pulse at the full laser repetition rate (90 MHz). These PRBS-patterned pulses serve as random structured illumination inside a one-dimensional (1D) spatial disperser. By multiplexing the PRBS patterns with a user-defined repetition period, the difference signal y_i=phi_i (x_i - x_{i-tau}) can be computed optically with balanced detection, where x is the image signal, phi_i is the PRBS pattern, and tau is the repetition period of the patterns. Two-dimensional (2D) image reconstruction via iterative alternating minimization to find the best locally-sparse representation yields an image of the edges in the flow direction, corresponding to the spatial and temporal 1D derivative. This provides both a favorable representation for image segmentation and a sparser representation for many objects that can improve image compression.
We present a method for full distortion elimination in phase-modulated analog optical links using the nonlinear optical process of four-wave mixing (FWM). Phase-modulated links consist of a laser and phase modulator in the transmitter and an interferometer (or local oscillator) and photodiode in the receiver. Phase modulation is a linear process, so distortion is introduced in the interferometric detection process. Quadrature biasing eliminates even-order distortion products, leaving only odd-order distortion. Here we introduce a method for eliminating these odd-order distortion products in the receiver. A small portion of the phase-modulated signal is tapped and combined with an unmodulated CW laser to seed a cascaded FWM comb source. This process generates an array of lightwaves with integer multiples of the signal’s phase modulation. By suitably scaling and combining these lightwaves with the original signal the overall transfer function of the interferometric receiver can be linearized (or given another tailored shape) through a Fourier synthesis approach. By combining a single lightwave from the generated comb with the original signal, we demonstrate the complete elimination of third-order distortion from the phase-modulated link leaving fifth-order distortion as the dominate source of distortion. We show a 17.6-dB SFDR improvement (1-Hz bandwidth) for a 6 GHz link operating at 5-mA total photocurrent and a 16.4-dB SFDR improvement (1-Hz bandwidth) for a 15 GHz link operating at 10-mA total photocurrent. By appropriately combining additional lightwaves from the generated comb, higher-order distortion products can be eliminated to produce an ideal linear (or custom shaped) transfer function.
We demonstrate an ultrahigh-rate imaging system applied to very high speed microscopic flows. Chirp processing of ultrafast laser pulses in optical fiber is employed to create pseudorandom spectral patterns at a rate of one unique pattern per pulse. These spectral patterns then serve as structured illumination of the object flows inside a 1D spatial disperser before digitization at a rate of one sample per optical pulse with a fast single pixel photodetector. Diffraction-limited microscopic imaging of flows up to 31.2 m/s is achieved at up to 19.8 and 39.6 Gigapixel/sec rates from a 720 MHz acquisition rate.
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