Lucky-region" fusion (LRF) is a synthetic imaging technique that has proven successful in enhancing the quality of images distorted by atmospheric turbulence. The LRF algorithm extracts sharp regions of an image obtained from a series of short exposure frames, and fuses the sharp regions into a final, improved image. In our previous research, the LRF algorithm had been implemented on a PC using the C programming language. However, the PC did not have sufficient processing power to handle real-time extraction, processing and reduction required when the LRF algorithm was applied to real-time video from fast, high-resolution image sensors rather than single picture images. This document describes a hardware implementation of the LRF algorithm on a VIRTEX-7 field programmable gate array (FPGA) to achieve real-time image processing. The novelty in our approach is the creation of a "black box" LRF video processing system with a general camera link input, a user controller interface, and a camera link or DVI video output. We also describe a custom hardware simulation environment we have built to test our LRF implementation.

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Certified electric vehicle power converters can inject DC current into the AC grid if they fail. Verification of DC injection by electric vehicle supply equipment can be a cost-effective extra measure to ensure power quality from a variety of plugged-in electric vehicles. As electric vehicle supply equipment typically performs high-accuracy revenue energy metering, we propose that measurement of AC current and DC injection with a single sensor is the most economically efficient design. This article presents an integrated shunt current sensing system with separation of AC and DC signals for concurrent revenue metering and DC injection detection. It also shows how the combined sensor is integrated into 19.2 kW single-phase electric vehicle supply equipment, and outlines how the design would be extended to 100 kW three-phase electric vehicle supply equipment. The prototype can detect DC injection of ≥400 mA in an AC current up to 80 A in accordance with the IEEE 1547-2018 standard. The prototype can also conduct revenue metering within the 1.0 accuracy class. The prototype does not have high power dissipation at high currents typical for shunt systems. Finally, the prototype is less costly than common electric vehicle supply equipment revenue metering CT systems with the addition of the popular Hall-effect sensor.

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