7 May 2017 Development of an embedded atmospheric turbulence mitigation engine
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Abstract
Methods to reconstruct pictures from imagery degraded by atmospheric turbulence have been under development for decades. The techniques were initially developed for observing astronomical phenomena from the Earth’s surface, but have more recently been modified for ground and air surveillance scenarios. Such applications can impose significant constraints on deployment options because they both increase the computational complexity of the algorithms themselves and often dictate a requirement for low size, weight, and power (SWaP) form factors. Consequently, embedded implementations must be developed that can perform the necessary computations on low-SWaP platforms. Fortunately, there is an emerging class of embedded processors driven by the mobile and ubiquitous computing industries. We have leveraged these processors to develop embedded versions of the core atmospheric correction engine found in our ATCOM software. In this paper, we will present our experience adapting our algorithms for embedded systems on a chip (SoCs), namely the NVIDIA Tegra that couples general-purpose ARM cores with their graphics processing unit (GPU) technology and the Xilinx Zynq which pairs similar ARM cores with their field-programmable gate array (FPGA) fabric.
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Aaron Paolini, James Bonnett, Stephen Kozacik, Eric Kelmelis, "Development of an embedded atmospheric turbulence mitigation engine", Proc. SPIE 10204, Long-Range Imaging II, 102040C (7 May 2017); doi: 10.1117/12.2263204; https://doi.org/10.1117/12.2263204
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