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
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.