Optical design and characterization of an advanced computational imaging system

Abstract

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.

From modeling to hardware: an experimental evaluation of image plane and Fourier plane coded compressive optical imaging

“…Structured illumination architectures ( Fig. 1(d)) use an SLM at a conjugateimage plane in the illumination path and follow the same generalized mathematical model as the IPC architecture [27]. Structured illumination microscopy techniques can even reach video rate imaging with better than diffraction limited resolution [28,29].…”

A review of snapshot multidimensional optical imaging: Measuring photon tags in parallel

“…The second strategy is based on passive imaging and therefore does not need a specialized light source. Within this category, representative techniques are parallel streak imaging using a tilted lenslet array [200], temporal pixel multiplexing [201], compressed ultrafast photography [27], coded aperture compressive temporal imaging [202], programmable pixel compressive imaging [13], and smart pixel imaging with computational-imaging arrays [203, 204]. …”

“…By contrast, smart pixel imaging (SPI) with computational-imaging arrays [203, 204] transfers this encoding process to the digital domain by using a digital-pixel focal plane array, thereby minimizing the signal-to-noise loss caused by physical encoding elements, such as the DMD in CUP and P2C2, and the absorption mask in CACTI. In SPI, each detector pixel can be modulated by a time-varying, pseudo-random, and dual-binary signal (−1,1 or 1,0) at a rate up to 100 MHz.…”

DMD Mask Construction to Suppress Blocky Structural Artifacts for Medium Wave Infrared Focal Plane Array-Based Compressive Imaging

“…where 16 ] T . In this work, to make the symbols clear and understandable, subscript is used to indicate the pixel position and superscript is for the number of the low-resolution MWIR image.…”

“…The compressed sampling process can be speeded up by using a focal plane array-based (FPA) sensor instead of the photodetector in SPC. Although the FPA CI systems have been implemented in visible [15,16] and short-wave infrared (SWIR) wavebands [17], comparatively few systems are implemented in MWIR. To our knowledge, only two experimental studies in the area of MWIR FPA CI are reported: Mahalanobis of Lockheed Martin built the first MWIR FPA CI system [18], which is a "merged-type", and we built a "separate-type" system [19].In spite of the acceleration of imaging speed, FPA CI has brought new challenges to the quality of reconstructed high-resolution images.…”