In an optical Line-of-Sight (LOS) scenario, such as one involving a LIDAR system, the goal is to recover an image of a target in the direct path of the transmitter and receiver. In Non-Line-of-Sight (NLOS) scenarios the target is hidden from both the transmitter and the receiver by an occluder, i.e. a wall. Recent advancements in technology, computer vision and inverse light transport theory have shown that it is possible to recover an image of a hidden target by exploiting the temporal information encoded in multiple-scattered photons. The core idea is to acquire data using an optical system, composed of an ultra-fast laser that emits short pulses (in the order of femtoseconds) and a camera capable of recovering the photons time-of-flight information (a typical resolution is in the order of picoseconds). We reconstruct 3D images from this data based on the backprojection algorithm, a method typically found in the computational tomography field, which is parallelizable and memory efficient, although it only provides an approximate solution. Here we present improved backprojection algorithms for applications to large scale scenes with with a large number of scatterers and meters to hundreds of meters diameter. We apply these methods to the NLOS imaging of rooms and lunar caves.
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