FPGA-based Neural Network for Nonuniformity Correction on Infrared Focal Plane Arrays

Despite recent technological advances which improve their performance and reduce their cost, Focal Plane Arrays for infrared imagers suffer from spatial nonuniformity that renders their output unusable unless a suitable correction method is applied. This paper describes an embedded hardware implementation of Scribner's algorithm for online nonuniformity correction. Our implementation on a Xilinx Spartan XC3S1200E FPGA achieves a throughput of more than 130 frames per second on 320x240-pixel IR video, which greatly exceeds real-time requirements. The power consumption of our system is 329mW, which is two orders of magnitude smaller than a software implementation of the algorithm on a traditional processor, and can be greatly reduced with a custom-VLSI implementation of the architecture.

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