Tianyi Mao

Adaptive compressed photon counting 3D imaging based on wavelet trees and depth map sparse representation

We demonstrate a photon counting 3D imaging system with short-pulsed structured illumination and a single-pixel photon counting detector. The proposed multiresolution photon counting 3D imaging technique acquires a high-resolution 3D image from a coarse image and details at successfully finer resolution sampled along the wavelet trees and their depth map sparse representations. Both the required measurements and the reconstruction time can be significant reduced, which makes the proposed technique suitable for scenes with high spatial resolution. The experimental results indicate that both the reflectivity and depth map of a scene at resolutions up to 512×512 pixels can be acquired and retrieved with practical times as low as 17.5 seconds. In addition, we demonstrate that this technique has ability to image in presence of partially-transmissive occluders, and to directly acquire novelty images to find changes in a scene.

Speckle-Shifting Ghost Imaging

In this paper, we introduce speckle-shifting ghost imaging (SSGI) which uses several corresponding shifted groups of speckle patterns instead of random speckle patterns in “computational ghost imaging” (CGI) to improve the performance of edge detection. The shifting of speckle patterns makes SSGI directly achieve the edges of an unknown object without the clear “ghost” images. Numerical simulations and experiments are performed. It is seen that SSGI is applicable for both binary and gray-scale objects in noisy environments. This provides a great opportunity to pave the way for the real applications of CGI in remote sensing and biological imaging.

Snapshot compressive spectral imaging based on adaptive coded apertures

Coded aperture snapshot spectral imager (CASSI) uses focal plane array (FPA) to capture three dimensional (3D) spectral scene by single or a few two-dimensional (2D) snapshots. Current CASSI systems use a set of fixed coded apertures to modulate the spatio-spectral data cube before the compressive measurement. This paper proposes an adaptive projection method to improve the compressive efficiency of the CASSI system by adaptively designing the coded aperture according to a-priori knowledge of the scene. The adaptive coded apertures are constructed from the nonlinear thresholding of the grey-scale map of the scene, which is captured by an aided RGB camera. Then, the 3D encoded spectral scene is projected onto the 2D FPAs. Based on the sparsity assumption, the spectral images can be reconstructed by the compressive sensing algorithm using the FPA measurements. This paper studies and verifies the proposed adaptive coded aperture method on a spatial super-resolution CASSI system, where the resolution of the coded aperture is higher than that of the FPAs. It is shown that the adaptive coded apertures provide superior reconstruction performance of the spectral images over the random coded apertures.

Optimization of coded aperture in compressive x-ray tomography

The CT system structure matrix in the coded aperture compressive X-ray tomography (CACXT) is highly structured and thus the random coded apertures are not optimal. A fast approach based on minimal information loss is proposed. The peak signal to noise ratios (PSNR) of the reconstructed images with optimized coded apertures exhibit significant gains and the design execution time is reduced by orders of magnitude. Simulations results for optimized coded apertures are shown, and their performance is compared to the use of random coded apertures.

Adaptive compressed photon counting 3D imaging based on wavelet trees and Hadamard multiplexing

A photon counting 3D imaging system with short-pulsed structured illumination and a single-pixel photon counting detector is built. The proposed multiresolution photon counting 3D imaging technique acquires a high-resolution 3D image from a coarse image and details at successfully finer resolution sampled by Hadamard multiplexing along with the wavelet trees. The detected power is significant increased thanks to the Hadamard multiplexing. Both the required measurements and the reconstruction time can be significant reduced, which makes the proposed technique suitable for scenes with high spatial resolution. Since the depth map is retrieved through a linear inverse Hadamard transform instead of the computational intensive optimization problems performed in CS, the time consumed to retrieve the depth map can be also reduced, and thus it will be suitable for applications of real-time compressed 3D imaging such as object tracking. Even though the resolution of the final 3D image can be high, the number of measurements remains small due to the adaptivity of the wavelet-trees-based sampling strategy. The adaptive sampling technique is quality oriented, allowing more control over the image quality. The experimental results indicate that both the intensity image and depth map of a scene at resolutions up to 512×512 pixels can be acquired and retrieved with practical times as low as 17 seconds.

Incoherent coincidence imaging of space objects

Incoherent Coincidence Imaging (ICI), which is based on the second or higher order correlation of fluctuating light field, has provided great potentialities with respect to standard conventional imaging. However, the deployment of reference arm limits its practical applications in the detection of space objects. In this article, an optical aperture synthesis with electronically connected single-pixel photo-detectors was proposed to remove the reference arm. The correlation in our proposed method is the second order correlation between the intensity fluctuations observed by any two detectors. With appropriate locations of single-pixel detectors, this second order correlation is simplified to absolute-square Fourier transform of source and the unknown object. We demonstrate the image recovery with the Gerchberg-Saxton-like algorithms and investigate the reconstruction quality of our approach. Numerical experiments has been made to show that both binary and gray-scale objects can be recovered. This proposed method provides an effective approach to promote detection of space objects and perhaps even the exo-planets.