Three-Dimensional Microscopic Image Reconstruction Based on Structured Light Illumination

In this paper, we propose and experimentally demonstrate a three-dimensional (3D) microscopic system that reconstructs a 3D image based on structured light illumination. The spatial pattern of the structured light changes according to the profile of the object, and by measuring the change, a 3D image of the object is reconstructed. The structured light is generated with a digital micro-mirror device (DMD), which controls the structured light pattern to change in a kHz rate and enables the system to record the 3D information in real time. The working distance of the imaging system is 9 cm at a resolution of 20 μm. The resolution, working distance, and real-time 3D imaging enable the system to be applied in bridge and road crack examinations, and structure fault detection of transportation infrastructures

Sub-Nyquist optical pulse sampling for photonic blind source separation

We propose and experimentally demonstrate an optical pulse sampling method for photonic blind source separation. The photonic system processes and separates wideband signals based on the statistical information of the mixed signals, and thus the sampling frequency can be orders of magnitude lower than the bandwidth of the signals. The ultra-fast optical pulses collect samples of the signals at very low sampling rates, and each sample is short enough to maintain the statistical properties of the signals. The low sampling frequency reduces the workloads of the analog to digital conversion and digital signal processing systems. In the meantime, the short pulse sampling maintains the accuracy of the sampled signals, so the statistical properties of the under-sampled signals are the same as the statistical properties of the original signals. The linear power range measurement shows that the sampling system with ultra-narrow optical pulse achieves a 30dB power dynamic range

Sub-Nyquist optical pulse sampling for photonic blind source separation

We propose and experimentally demonstrate an optical pulse sampling method for photonic blind source separation. The photonic system processes and separates wideband signals based on the statistical information of the mixed signals, and thus the sampling frequency can be orders of magnitude lower than the bandwidth of the signals. The ultra-fast optical pulses collect samples of the signals at very low sampling rates, and each sample is short enough to maintain the statistical properties of the signals. The low sampling frequency reduces the workloads of the analog to digital conversion and digital signal processing systems. In the meantime, the short pulse sampling maintains the accuracy of the sampled signals, so the statistical properties of the under-sampled signals are the same as the statistical properties of the original signals. The linear power range measurement shows that the sampling system with ultra-narrow optical pulse achieves a 30dB power dynamic range

Selective disinfection based on directional ultraviolet irradiation and artificial intelligence

Ultraviolet disinfection has been proven to be effective for surface sanitation. Traditional ultraviolet disinfection systems generate omnidirectional radiation, which introduces safety concerns regarding human exposure. Large scale disinfection must be performed without humans present, which limits the time efficiency of disinfection. We propose and experimentally demonstrate a targeted ultraviolet disinfection system using a combination of robotics, lasers, and deep learning. The system uses a laser-galvo and a camera mounted on a two-axis gimbal running a custom deep learning algorithm. This allows ultraviolet radiation to be applied to any surface in the room where it is mounted, and the algorithm ensures that the laser targets the desired surfaces avoids others such as humans. Both the laser-galvo and the deep learning algorithm were tested for targeted disinfection

Wideband Mixed Signal Separation Based on Photonic Signal Processing

The growing needs for high-speed and secure communications create an increasing challenge to the contemporary framework of signal processing. The coexistence of multiple high-speed wireless communication systems generates wideband interference. To protect the security and especially the privacy of users’ communications requires stealth communication that hides and recovers private information against eavesdropping attacks. The major problem in interference management and stealth information recovery is to separate the signal of interest from wideband interference/noise. However, the increasing signal bandwidth presents a real challenge to existing capabilities in separating the mixed signal and results in unacceptable latency. The photonic circuit processes a signal in an analog way with a unanimous frequency response over GHz bandwidth. The digital processor measures the statistical patterns of the signals with sampling rate orders of magnitude smaller than the Nyquist frequency. Under-sampling the signals significantly reduces the workload of the digital processor while providing accurate control of the photonic circuit to perform the real-time signal separations. The wideband mixed signal separation, based on photonic signal processing is scalable to multiple stages with the performance of each stage accrued

Wideband Mixed Signal Separation Based on Photonic Signal Processing

The growing needs for high-speed and secure communications create an increasing challenge to the contemporary framework of signal processing. The coexistence of multiple high-speed wireless communication systems generates wideband interference. To protect the security and especially the privacy of users’ communications requires stealth communication that hides and recovers private information against eavesdropping attacks. The major problem in interference management and stealth information recovery is to separate the signal of interest from wideband interference/noise. However, the increasing signal bandwidth presents a real challenge to existing capabilities in separating the mixed signal and results in unacceptable latency. The photonic circuit processes a signal in an analog way with a unanimous frequency response over GHz bandwidth. The digital processor measures the statistical patterns of the signals with sampling rate orders of magnitude smaller than the Nyquist frequency. Under-sampling the signals significantly reduces the workload of the digital processor while providing accurate control of the photonic circuit to perform the real-time signal separations. The wideband mixed signal separation, based on photonic signal processing is scalable to multiple stages with the performance of each stage accrued