FPGA emulation of a spike-based, stochastic system for real-time image dewarping

Image dewarping is vital for systems performing image processing tasks in real-time. We introduce a real-time emulation of a low-power, event-based system for image dewarping implemented on an FPGA. The system utilizes stochastic computation in conjunction with a neuromorphic system called the Integrate-and-Fire Array Transceiver (IFAT) for low hardware area and to reduce computational complexity. It models the dynamics of integrate-and-fire neurons and takes advantage of the reconfigurability of the IFAT system for performing image dewarping in real-time. When real-time camera motion data is readily available, we show that this system can accurately perform the dewarping task. Such a system is ideal for devices such as micro aerial vehicles performing visual processing tasks in-flight.