Synthetic Aperture Imaging with Neural Signal Representations

Synthetic aperture imaging is a powerful computational imaging technique wherein a collection of low resolution measurements are computationally integrated into a single high-resolution image. This fusion step has been traditionally accomplished with pixel-based scene representations. This manuscript provides an overview of neural signal representations and describes how they can be used to enhance the synthetic aperture reconstruction pipeline.