Availability of off-the-shelf infrared sensors combined with high definition visible cameras has made possible the construction of a Software Defined Multi-Spectral Imager (SDMSI) combining long-wave, near-infrared and visible imaging. The SDMSI requires a real-time embedded processor to fuse images and to create real-time depth maps for opportunistic uplink in sensor networks. Researchers at Embry Riddle Aeronautical University working with University of Alaska Anchorage at the Arctic Domain Awareness Center and the University of Colorado Boulder have built several versions of a low-cost drop-in-place SDMSI to test alternatives for power efficient image fusion. The SDMSI is intended for use in field applications including marine security, search and rescue operations and environmental surveys in the Arctic region. Based on Arctic marine sensor network mission goals, the team has designed the SDMSI to include features to rank images based on saliency and to provide on camera fusion and depth mapping. A major challenge has been the design of the camera computing system to operate within a 10 to 20 Watt power budget. This paper presents a power analysis of three options: 1) multi-core, 2) field programmable gate array with multi-core, and 3) graphics processing units with multi-core. For each test, power consumed for common fusion workloads has been measured at a range of frame rates and resolutions. Detailed analyses from our power efficiency comparison for workloads specific to stereo depth mapping and sensor fusion are summarized. Preliminary mission feasibility results from testing with off-the-shelf long-wave infrared and visible cameras in Alaska and Arizona are also summarized to demonstrate the value of the SDMSI for applications such as ice tracking, ocean color, soil moisture, animal and marine vessel detection and tracking. The goal is to select the most power efficient solution for the SDMSI for use on UAVs (Unoccupied Aerial Vehicles) and other drop-in-place installations in the Arctic. The prototype selected will be field tested in Alaska in the summer of 2016.
Researchers at the University of Alaska Anchorage and University of Colorado Boulder have built a low cost high
performance and efficiency drop-in-place Computational Photometer (CP) to test in field applications ranging from port
security and safety monitoring to environmental compliance monitoring and surveying. The CP integrates off-the-shelf
visible spectrum cameras with near to long wavelength infrared detectors and high resolution digital snapshots in a
single device. The proof of concept combines three or more detectors into a single multichannel imaging system that can
time correlate read-out, capture, and image process all of the channels concurrently with high performance and energy
efficiency. The dual-channel continuous read-out is combined with a third high definition digital snapshot capability and
has been designed using an FPGA (Field Programmable Gate Array) to capture, decimate, down-convert, re-encode, and
transform images from two standard definition CCD (Charge Coupled Device) cameras at 30Hz. The continuous stereo
vision can be time correlated to megapixel high definition snapshots. This proof of concept has been fabricated as a fourlayer
PCB (Printed Circuit Board) suitable for use in education and research for low cost high efficiency field
monitoring applications that need multispectral and three dimensional imaging capabilities. Initial testing is in progress
and includes field testing in ports, potential test flights in un-manned aerial systems, and future planned missions to
image harsh environments in the arctic including volcanic plumes, ice formation, and arctic marine life.