HW/SW Implementation of Hyperspectral Target Detection Algorithm

Hyperspectral images obtained by imaging spectrometer contain a vast amount of data which require techniques such as target detection to extract useful information. This article presents an implementation of the target detection method Adaptive Cosine Estimator (ACE) for hyperspectral images. The algorithm is implemented as hardware-software partitioned system on Zynq-7000 development platform. The computationally intensive operations are accelerated on FPGA with the speedup factor of 28.54. The timing analysis presents results for the partitioned system as well as for the software implementation on Zynq processing system used for comparison. The detection performance of the implemented algorithm is tested and verified using publicly available hyperspectral scenes with ground truth data.