Abstract
We demonstrate numerically the discrete image recovery via stochastic resonance in optically induced photonic lattices. The underlying signals are regularly reinforced at the expense of scattering noise with the interplay of the periodic potentials and the self-focusing nonlinearity. We founded that the energy redistribution tends to be periodic and the signal reinforcement is promoted with the help of periodic potentials. The lattice intensity levels, applied voltages, and correlation lengths are important parameters to influence the recovery effects. The dynamic nonlinear evolution including intensity and power spectrum is modeled according to the two-dimensional quasi-particle motion model. Our results suggest a potential technology to detect the noisy images.
Highlights
Imaging through scattering media, such as smokes, tissues, and cloudy water, is one of the fundamental problems in optics
The results suggest that the weak periodic potentials promote the periodic localization of the light beam
The discrete image recovery via stochastic resonance (SR) has been numerically demonstrated in optically induced photonic lattices
Summary
Imaging through scattering media, such as smokes, tissues, and cloudy water, is one of the fundamental problems in optics. Conventional optical imaging technologies, such as spatial filtering, polarization discrimination, and time gating, intuitively improve image quality by rejecting the detrimental noise[1,2,3]. These technologies are limited because some valuable signals accompanying with noise are inevitably prevented. The coherent signals are enhanced at the expense of incoherent noise by seeding modulation instability under the self-focusing nonlinearity. We demonstrate numerically the discrete image recovery via SR in optically induced photonic lattices. The underlying signals, as a source of instability, are regularly enhanced at the expense of scattering noise under the discrete self-focusing nonlinearity. Our results indicate a potential method for recovering scattering images in various imaging applications
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