Computational photography and compressive holography

As lasers, photosensors, and computational imaging techniques improve, holography becomes an increasingly attractive approach for imaging applications largely re- served for photography. For the same illumination energy, we show that holography and photography have nearly identical noise performance. Because the coherent field is two dimensional outside of a source, there is ambiguity in inferring the three-dimensional structure of a source from the coherent field. Compressive holography overcomes this limitation by imposing sparsity constraints on the three- dimensional scatterer, which greatly reduces the number of possibilities allowing reliable inference of structure. We demonstrate the use of compressive holography to infer the three-dimensional structure of a scene comprising two toys