A single exposure superresolution (SR) restoration algorithm for an optical sparse aperture (OSA) imaging system based on random convolution is proposed. The low-resolution image from the OSA system is restored by adding a set of incoherent measurements taken using random convolution architecture, in which there is a random phase mask in the Fourier plane and a random amplitude mask in the image plane in the conventional optical 4f system. Both masks are generated by chaotic maps. The simulation results show that this algorithm can effectively recover the images degraded by both optical diffraction effect and geometrical limited resolution under noisy and aberrated conditions. The spatial resolution gain factor is above 2.82 without subsampling and 1.26 with subsampling. Moreover, it can obtain a better restoration quality than traditional algorithms by optimizing the initial conditions of chaotic maps.
We report a chaotic optical time-domain reflectometry for fiber fault location, where a chaotic probe signal is generated by driving a distributed feedback laser diode with an improved Colpitts chaotic oscillator. The results show that the unterminated fiber end, the loose connector, and the mismatch connector can be precisely located. A measurement range of approximately 91 km and a range independent resolution of 6 cm are achieved. This implementation method is easy to integrate and is cost effective, which gives it great potential for commercial applications.
Aperture synthesis imaging has been proved to be attractive in surveillance and detection applications. Such an imaging process is inevitably subject to aberrations introduced by instrument defects and/or turbulent media. Redundant spacing calibration (RSC) technique allows continuous calibration of these errors at any electromagnetic wavelength. However, it is based on specially designed array, in which just enough redundancy is included to permit the successful implementation of RSC. A new design criterion for linear RSC array is described, which introduces coverage efficiency and redundancy efficiency factors, aiming to find the perfect configurations, which have as complete uv-plane coverage as possible while containing required redundancy. Optimum linear arrays for N (number of subapertures) up to 10 are listed based on simulated annealing algorithm. The comparisons with existing linear RSC arrays with equivalent subaperture number are implemented. Results show that the optimized arrays have better performance of both optical transfer function, point spread function, and object reconstruction with reasonable value of the matrix condition number. After that, linear arrays are used to construct two-dimensional (2-D) pseudo-Y-shaped RSC arrays, which give a way to design 2-D RSC arrays without exhaustive searches.
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