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.
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 (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.