Mr. James Tidman Profile

James Tidman

at InView Technology Corp

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Proceedings Article | 26 September 2013 Paper

Compact opto-electronic engine for high-speed compressive sensing

James Tidman, Tyler Weston, Donna Hewitt, Matthew Herman, Lenore McMackin

Proceedings Volume 8856, 885616 (2013) https://doi.org/10.1117/12.2024148

KEYWORDS: Sensors, Digital micromirror devices, Cameras, Mirrors, Modulation, Imaging systems, Modulators, Field programmable gate arrays, Capacitance, Calibration

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The measurement efficiency of Compressive Sensing (CS) enables the computational construction of images from far fewer measurements than what is usually considered necessary by the Nyquist– Shannon sampling theorem. There is now a vast literature around CS mathematics and applications since the development of its theoretical principles about a decade ago. Applications include quantum information to optical microscopy to seismic and hyper-spectral imaging. In the application of shortwave infrared imaging, InView has developed cameras based on the CS single-pixel camera architecture. This architecture is comprised of an objective lens to image the scene onto a Texas Instruments DLP® Micromirror Device (DMD), which by using its individually controllable mirrors, modulates the image with a selected basis set. The intensity of the modulated image is then recorded by a single detector. While the design of a CS camera is straightforward conceptually, its commercial implementation requires significant development effort in optics, electronics, hardware and software, particularly if high efficiency and high-speed operation are required. In this paper, we describe the development of a high-speed CS engine as implemented in a lab-ready workstation. In this engine, configurable measurement patterns are loaded into the DMD at speeds up to 31.5 kHz. The engine supports custom reconstruction algorithms that can be quickly implemented. Our work includes optical path design, Field programmable Gate Arrays for DMD pattern generation, and circuit boards for front end data acquisition, ADC and system control, all packaged in a compact workstation.

Proceedings Article | 31 May 2013 Paper

A higher-speed compressive sensing camera through multi-diode design

Matthew Herman, James Tidman, Donna Hewitt, Tyler Weston, Lenore McMackin

Proceedings Volume 8717, 871706 (2013) https://doi.org/10.1117/12.2015745

KEYWORDS: Cameras, Digital micromirror devices, Sensors, Mirrors, Modulation, Diodes, Reconstruction algorithms, Compressed sensing, Photodiodes, Imaging systems

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Obtaining high frame rates is a challenge with compressive sensing (CS) systems that gather measurements in a sequential manner, such as the single-pixel CS camera. One strategy for increasing the frame rate is to divide the FOV into smaller areas that are sampled and reconstructed in parallel. Following this strategy, InView has developed a multi-aperture CS camera using an 8×4 array of photodiodes that essentially act as 32 individual simultaneously operating single-pixel cameras. Images reconstructed from each of the photodiode measurements are stitched together to form the full FOV. To account for crosstalk between the sub-apertures, novel modulation patterns have been developed to allow neighboring sub-apertures to share energy. Regions of overlap not only account for crosstalk energy that would otherwise be reconstructed as noise, but they also allow for tolerance in the alignment of the DMD to the lenslet array. Currently, the multi-aperture camera is built into a computational imaging workstation configuration useful for research and development purposes. In this configuration, modulation patterns are generated in a CPU and sent to the DMD via PCI express, which allows the operator to develop and change the patterns used in the data acquisition step. The sensor data is collected and then streamed to the workstation via an Ethernet or USB connection for the reconstruction step. Depending on the amount of data taken and the amount of overlap between sub-apertures, frame rates of 2–5 frames per second can be achieved. In a stand-alone camera platform, currently in development, pattern generation and reconstruction will be implemented on-board.

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