We describe an advanced computational imaging system with an optical architecture that enables simultaneous and dynamic pupil-plane and image-plane coding accommodating several task-specific applications. We assess the optical requirement trades associated with custom and commercial-off-the-shelf (COTS) optics and converge on the development of two low-cost and robust COTS testbeds. The first is a coded-aperture programmable pixel imager employing a digital micromirror device (DMD) for image plane per-pixel oversampling and spatial super-resolution experiments. The second is a simultaneous pupil-encoded and time-encoded imager employing a DMD for pupil apodization or a deformable mirror for wavefront coding experiments. These two testbeds are built to leverage two MIT Lincoln Laboratory focal plane arrays – an orthogonal transfer CCD with non-uniform pixel sampling and on-chip dithering and a digital readout integrated circuit (DROIC) with advanced on-chip per-pixel processing capabilities. This paper discusses the derivation of optical component requirements, optical design metrics, and performance analyses for the two testbeds built.
Smart pixel imaging with computational-imaging arrays (SPICA) transfers image plane coding typically realized in the optical architecture to the digital domain of the focal plane array, thereby minimizing signal-to-noise losses associated with static filters or apertures and inherent diffraction concerns. MIT Lincoln Laboratory has been developing digitalpixel focal plane array (DFPA) devices for many years. In this work, we leverage legacy designs modified with new features to realize a computational imaging array (CIA) with advanced pixel-processing capabilities. We briefly review the use of DFPAs for on-chip background removal and image plane filtering. We focus on two digital readout integrated circuits (DROICS) as CIAs for two-dimensional (2D) transient target tracking and three-dimensional (3D) transient target estimation using per-pixel coded-apertures or flutter shutters. This paper describes two DROICs – a SWIR pixelprocessing imager (SWIR-PPI) and a Visible CIA (VISCIA). SWIR-PPI is a DROIC with a 1 kHz global frame rate with a maximum per-pixel shuttering rate of 100 MHz, such that each pixel can be modulated by a time-varying, pseudorandom, and duo-binary signal (+1,-1,0). Combining per-pixel time-domain coding and processing enables 3D (x,y,t) target estimation with limited loss of spatial resolution. We evaluate structured and pseudo-random encoding strategies and employ linear inversion and non-linear inversion using total-variation minimization to estimate a 3D data cube from a single 2D temporally-encoded measurement. The VISCIA DROIC, while low-resolution, has a 6 kHz global frame rate and simultaneously encodes eight periodic or aperiodic transient target signatures at a maximum rate of 50 MHz using eight 8-bit counters. By transferring pixel-based image plane coding to the DROIC and utilizing sophisticated processing, our CIAs enable on-chip temporal super-resolution.
A digital pixel CMOS focal plane array has been developed to enable low latency implementations of image processing systems such as centroid trackers, Shack-Hartman wavefront sensors, and Fitts correlation trackers through the use of in-pixel digital signal processing (DSP) and generic parallel pipelined multiply accumulate (MAC) units. Light intensity digitization occurs at the pixel level, enabling in-pixel DSP and noiseless data transfer from the pixel array to the peripheral processing units. The pipelined processing of row and column image data prior to off chip readout reduces the required output bandwidth of the image sensor, thus reducing the latency of computations necessary to implement various image processing systems. Data volume reductions of over 80% lead to sub 10μs latency for completing various tracking and sensor algorithms. This paper details the architecture of the pixel-processing imager (PPI) and presents some initial results from a prototype device fabricated in a standard 65nm CMOS process hybridized to a commercial off-the-shelf short-wave infrared (SWIR) detector array.
This paper describes an active millimeter-wave (MMW) holographic imaging system used for the study of compressive
measurement for concealed weapons detection. We record a digitized on-axis, Gabor hologram using a single pixel
incoherent receiver that is translated at the detector plane to form an image composite. Capturing measurements in the
MMW regime can be costly since receiver circuits are expensive and scanning systems can be plagued by their long data
acquisition times. Thus, we leverage recent advances in compressive sensing with a traditional holographic method in
order to estimate a 3D (x,y,z) object distribution from a 2D recorded image composite. To do this, we minimize a convex
quadratic function using total variation (TV) regularization. Gabor holograms are recorded of semi-transparent objects,
in the MMW, mimicking weapons and other objects. We present preliminary results of 3D reconstructions of objects at
various depths estimated from a 2D recorded hologram. We compare backpropagation results with our decompressive
inference algorithm. A possible application includes remote concealed weapons detection at security checkpoints.
This paper describes the application of a coded aperture snapshot spectral imager (CASSI) to fluorescence microscopy. CASSI records an interleaved spatially varying, spectrally filtered map of an object on a 2D focal plane. Convex optimization techniques combining least squares QR factorization with a total variance constraint are used to reconstruct a 3D data cube from a spectrally encoded 2D scene. CASSI records a 3D dataset at video rate - making it suitable for dynamic cellular imaging. We report on the reconstruction of fluorescent microspheres used in fluorescence microscopy applications and compare the results with images from a multi-spectral confocal system.