We present a novel speckle reduction scheme for application in laser-based projection systems. The scheme combines the use of a microlens array (MLA) as screen material with the concept of reduced spatial coherence. Incorporating the screen in the speckle reduction process reduces laser projector cost and complexity. On a typical screen, random scattering of coherent light would cause random interference, i.e. speckle. On an MLA screen however, the interference between the fields emitted by different microlenses is inhibited if the spatial coherence area of the incident light is made smaller than the microlens footprint. We tested both a MLA with randomly arranged lenses of varying size, averaging 120 μm in diameter, and a MLA with regularly spaced lenses with a fixed diameter of 100 μm. We benchmarked the performance of these MLA screens and a regular diffusive screen. Using a small-scale projection setup with a CCD camera as observer, we experimentally quantified the speckle contrast observed on these screens. Objective speckle contrast measurements on the irregular MLA yield results close to the subjective human speckle detection limit. Besides the experimental validation of the proposed speckle reduction scheme, we constructed a quantitative model to describe the speckle characteristics of the different screens. The model corresponds very well with experimental results and allows us to quantify the relative contributions of the different speckle reduction processes at play. Our approach can benefit any laser-based projection system, such as for example 3D cinema.
We present numerical results on a spatially parallel photonic reservoir computer. In this computing paradigm, an input signal couples to a randomly interconnected reservoir of state variables (neurons). The reservoirs output is constructed by combining the neural responses with different weights, and is used to perform useful computation. Reservoir computers are easy to train as only these output weights are optimize while keeping internal connections fixed. We are currently building a bulk optics high bandwidth reservoir computer where neurons are encoded using the spatial degree of freedom of light. We use a linear Fabry-Prot resonator as reservoir and implement a nonlinear readout layer. New input samples are injected every 2ns. The neurons are encoded as a grid of 9 by 9 spots in the 2-dimensional transverse spatial extent of the cavity input coupler. We place a lens in the middle of the resonator with focal length half the resonator length, so that the conjugate plane of the neuron grid is on the resonator back plane. At this end, a phase-only spatial light modulator acts as a programmable diffraction grating, mixing the spatial modes in the resonator. We have simulated the optical reservoir and an electronic nonlinear output layer. These simulations were performed in discrete time, and take into account photodetector noise. We study the effect of the diffractive coupling scheme and its symmetry on the simulated reservoir computing performance on a standard benchmark test. We find that symmetry improve noise robustness at the expense of diversity in the neural responses.