Xin Yuan

Structured illumination temporal compressive microscopy

We present a compressive video microscope based on structured illumination with incoherent light source. The source-side illumination coding scheme allows the emission photons being collected by the full aperture of the microscope objective, and thus is suitable for the fluorescence readout mode. A 2-step iterative reconstruction algorithm, termed BWISE, has been developed to address the mismatch between the illumination pattern size and the detector pixel size. Image sequences with a temporal compression ratio of 4:1 were demonstrated.

High-speed compressive range imaging based on active illumination.

We report a compressive imaging method based on active illumination, which reconstructs a 3D scene at a frame rate beyond the acquisition speed limit of the camera. We have built an imaging prototype that projects temporally varying illumination pattern and demonstrated a joint reconstruction algorithm that iteratively retrieves both the range and high-temporal-frequency information from the 2D low-frame rate measurement. The reflectance and depth-map videos have been reconstructed at 1000 frames per second (fps) from the measurement captured at 200 fps. The range resolution is in agreement with the resolution calculated from the triangulation methods based on the same system geometry. We expect such an imaging method could become a simple solution to a wide range of applications, including industrial metrology, 3D printing, and vehicle navigations.

Compressive high-speed stereo imaging

A compressive high-speed stereo imaging system is reported. The system is capable of reconstructing 3D videos at a frame rate 10 times higher than the sampling rate of the imaging sensors. An asymmetric configuration of stereo imaging system has been implemented by including a high-speed spatial modulator in one of the binocular views, and leaving the other view unchanged. We have developed a two-step reconstruction algorithm to recover the irradiance and depth information of the high-speed scene. The experimental results have demonstrated high-speed video reconstruction at 800fps from 80fps measurements. The reported compressive stereo imaging method does not require active illumination, offering a robust yet inexpensive solution to high-speed 3D imaging.

Noise adaptive wavelet thresholding for speckle noise removal in optical coherence tomography

Optical coherence tomography (OCT) is based on coherence detection of interferometric signals and hence inevitably suffers from speckle noise. To remove speckle noise in OCT images, wavelet domain thresholding has demonstrated significant advantages in suppressing noise magnitude while preserving image sharpness. However, speckle noise in OCT images has different characteristics in different spatial scales, which has not been considered in previous applications of wavelet domain thresholding. In this study, we demonstrate a noise adaptive wavelet thresholding (NAWT) algorithm that exploits the difference of noise characteristics in different wavelet sub-bands. The algorithm is simple, fast, effective and is closely related to the physical origin of speckle noise in OCT image. Our results demonstrate that NAWT outperforms conventional wavelet thresholding.

Compressive video sensing with side information

Our temporally compressive imaging system reconstructs a high-speed image sequence from a single, coded snapshot. The reconstruction quality, similar to that of other compressive sensing systems, often depends on the structure of the measurement, as well as the choice of regularization. In this paper, we report a compressive video system that also captures the side information to aid in the reconstruction of high-speed scenes. The integration of the side information not only improves the quality of reconstruction, but also reduces the dependence of the reconstruction on regularization. We have implemented a system prototype that splits the field of view of a single camera into two channels: one channel captures the coded, low-frame-rate measurement for high-speed video reconstruction, and the other channel captures a direct measurement without coding as the side information. A joint reconstruction model is developed to recover the high-speed videos from the two channels. By analyzing both the experimental and the simulation results, the reconstructions with side information have demonstrated superior performances in terms of both the peak signal-to-noise ratio and structural similarity.

Video compressed imaging using side information (Rising Researcher Presentation) (Conference Presentation)

Video compressive imaging system reconstructs high-speed image sequence from a single, coded snapshot. In this paper, we report a compressive video sensing system that captures the side information in addition to the main measurement to aid the reconstruction of high-speed scenes. The integration of the side information not only improves the quality of reconstruction, but also reduces the dependence of the reconstruction on regularization. We have implemented a system prototype, which splits the field of view of a single camera into two channels: one channel captures the coded, low-frame-rate measurement for high speed video reconstruction; the other channel captures a direct measurement without coding as the side information. A joint reconstruction model is developed to recover the high-speed videos from the two channels.

Compressive temporal stereo-vision imaging

We report a binocular stereo-vision imaging system acquiring videos exceeding the cameras’ frame rate. An iterative reconstruction algorithm with the knowledge of the correspondence between the cameras demonstrated a 4x faster frame rate in simulation.

Compressive Temporal RGB-D Imaging

We report a compressive imaging system for high-speed color (RGB) video and range sensing based on the structured illumination. Random patterns are projected on the scene at a higher frame rate than that of the color camera. High-speed RGB-D scenes are reconstructed from a single 2D measurement via efficient algorithms.