Computational ghost imaging is a technique that enables lensless single-pixel detectors to produce images. By illuminating a scene with a series of patterns from a digital light projector (DLP) and measuring the reflected or transmitted intensity, it is possible to retrieve a two-dimensional (2D) image when using a suitable computer algorithm. An important feature of this approach is that although the light travels from the DLP and is measured by the detector, the images produced reveal that the detector behaves like a source of light and the DLP behaves like a camera. By placing multiple single-pixel detectors in different locations it is possible to obtain multiple ghost images with different shading profiles, which together can be used to accurately calculate the three-dimensional (3D) surface geometry through a photometric stereo techniques. In this work we show that using four photodiodes and a 850nm source of illumination, high quality 3D images of a large toy soldier can be retrieved. The use of simplified lensless detectors in 3D imaging allows different detector materials and architectures to be used whose sensitivity may extend beyond the visible spectrum, at wavelengths where existing camera based technology can become expensive or unsuitable.
The field of ghost imaging encompasses systems which can retrieve the spatial information of an object through correlated measurements of a projected light field, having spatial resolution, and the associated reflected or transmitted light intensity measured by a photodetector. By employing a digital light projector in a computational ghost imaging system with multiple spectrally filtered photodetectors we obtain high-quality multi-wavelength reconstructions of real macroscopic objects. We compare different reconstruction algorithms and reveal the use of compressive sensing techniques for achieving sub-Nyquist performance. Furthermore, we demonstrate the use of this technology in non-visible and fluorescence imaging applications.