Multimodal registration of visible, SWIR and LWIR images in a distributed smart camera system

We present a multimodal registration algorithm between images in the visible, short-wave infrared and long-wave infrared spectra. The algorithm works with two reference-objective image pairs and operates in two stages: (1) A calibration phase between static frames to estimate the transformation parameters using histogram of oriented gradients and the Chi-square distance; (2) a frame-by-frame mapping with these parameters using a projective transformation and a bilinear interpolation to map the objective video stream to the coordinate system of the reference video stream. We present a distributed heterogeneous architecture that combines a programmable processor core and a custom hardware accelerator for each node. The software performs the calibration phase, whereas the hardware computes the frame-by-frame mapping. We implemented our design using a Xilinx Zynq XC7Z020 system-on-a-chip for each node. The prototype uses 2.38W of power, 25% of the logic resources and 65% of the available on-chip memory per node. Running at 100MHz, the core can register 640 × 512-pixel frames in 4ms after initial calibration, which allows our module to operate at up to 250 frames per second.