In order to investigate changes of forest biomass, scientists use microwave tomography to image the vegetation. At the smallest scale, individual plants can be imaged to investigate branching and growth, but even synthetic aperture radar can reveal large-scale changes in regional ecology. To the right, you can see the experimental setup to image an individual plant.
Filtered back-projection is at the core of all of these techniques: using the inverse Radon transform to reconstruct regular images from Fourier samples. Below you can see the final reconstructed image. Since these samples are often not on a uniform Cartesian grid, the non-uniform version of the FFT comes into play (NUFFT), and all of this requires some serious number crunching: bring in the GPU.
Based on their earlier experience using Jacket to prototype antenna arrays, Drs. Capozzoli, Curcio, di Vico, and Liseno developed a parallel implementation of NUFFT suited for GPUs. Their work was published in IEICE Transactions on Communications. As their paper details, NUFFT sampling and reconstruction rely heavily on interpolation and FFT — two things that NVIDIA GPUs are great at. Evaluating the performance of various sampling schemes and parallelization techniques, they report speedups reaching 10x as compared to an 8-core CPU.
Thanks to Drs. Capozzoli, Curcio, di Vico, and Liseno for once again sharing their work!