Deep convolutional neural networks (DCNNs) offer a promising performance for many image processing areas, such as super-resolution, deconvolution, image classification, denoising, and segmentation, with outstanding results. Here, we develop for the first time, to our knowledge, a method to perform 3-D computational optical tomography using 3-D DCNN. A simulated 3-D phantom dataset was first constructed and converted to a dataset of phase objects imaged on a spatial light modulator. For each phase image in the dataset, the corresponding diffracted intensity image was experimentally recorded on a CCD. We then experimentally demonstrate the ability of the developed 3-D DCNN algorithm to solve the inverse problem by reconstructing the 3-D index of refraction distributions of test phantoms from the dataset from their corresponding diffraction patterns.
This paper utilizes a synchronized Lorenz chaotic drive/response system, which uses Haar filtering and appropriate thresholding in order to detect a transmitted random binary message. Using the Lorenz chaotic attractor to obscure the message, the transmission is passed through an Additive White Gaussian (AWG) channel to successfully retrieve the original binary random data. The detection mechanism employs the Haar Wavelet Transform in combating the channel noise. A communication technique using Chaotic Parameter Modulation (CPM) is simulated in Matlab and prototyped on a reconfigurable hardware platform from Xilinx.
Proc. SPIE. 9080, Laser Radar Technology and Applications XIX; and Atmospheric Propagation XI
KEYWORDS: Signal to noise ratio, Optical filters, Wavelets, Interference (communication), Field programmable gate arrays, Telecommunications, Free space optics, Binary data, Prototyping, Free space optical communications
High bandwidth, fast deployment with relatively low cost implementation are some of the important advantages of free space optical (FSO) communications. However, the atmospheric turbulence has a substantial impact on the quality of a laser beam propagating through the atmosphere. A new method was presented in  and  to perform bit synchronization and detection of binary Non-Return-to-Zero (NRZ) data from a free-space optical (FSO) communication link. It was shown that, when the data is binary NRZ with no modulation, the Haar wavelet transformation can effectively reduce the scintillation noise. In this paper, we leverage and modify the work presented in  in order to provide a real-time streaming hardware prototype. The applicability of these concepts will be demonstrated through providing the hardware prototype using one of the state-of-the-art reconfigurable hardware, namely Field Programmable Gate Arrays, and highly productive high-level design tools such as System Generator for DSP from Xilinx.