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Computer vision is increasingly used in areas such as unmanned vehicles, surveillance systems and remote sensing. However, in foggy scenarios, image degradation leads to loss of target details, which seriously affects the accuracy and effectiveness of these vision tasks. Polarized light, due to the fact that its electromagnetic waves vibrate in a specific direction, is able to resist scattering and refraction effects in complex media more effectively compared to unpolarized light. As a result, polarized light has a greater ability to maintain its polarization characteristics in complex transmission media and under long-distance imaging conditions. This property makes polarized imaging especially suitable for complex scenes such as outdoor and underwater, especially in foggy environments, where higher quality images can be obtained. Based on this advantage, we propose an innovative semi-physical polarization dehazing method that does not rely on an external light source. The method simulates the diffusion process of fog and designs a diffusion kernel that corresponds to the image blurriness caused by this diffusion. By employing spatiotemporal Fourier transforms and deconvolution operations, the method recovers the state of fog droplets prior to diffusion and the light inversion distribution of objects. This approach effectively achieves dehazing and detail enhancement of the scene.

We investigate the nonlinear magneto-optical response in non-centrosymmetric magnetic Weyl semimetals featuring a quadratic tilt, focusing particularly on the influence of the van Hove singularity (VHS). In the absence of a magnetic field, the second-order nonlinear Drude conductivity components exhibit inflection or dip behavior across the VHS. In contrast, the second-order nonlinear anomalous Hall conductivity, primarily governed by the Berry curvature dipole, manifests a subtle plateau-like structure. As the tilt strength increases, the VHS energy escalates, thereby amplifying the VHS-induced characteristics within these second-order conductivity components. However, in the presence of a magnetic field, we show that the resultant magnetic moment suppresses nonlinear electron transport while enhancing nonlinear hole transport. %both suppresses and notably enhances nonlinear magnetic-optical transport in the electron and hole regions, respectively. This effect serves to mitigate the impact of the VHS, resulting specifically in an asymmetric peak or a kinked-like structure in the magnetic field-induced contribution to the second-order nonlinear conductivity near the Weyl nodes. These findings provide new insights into the intricate interplay among the VHS, Berry curvature, and magnetic moment in nonlinear magneto-optical transport through non-centrosymmetric magnetic Weyl semimetals., Comment: 10 pages, 5 figures. Accepted for publication in Phys. Rev. B

The detected frequency response range of phase-sensitive optical time domain reflectometry is limited by the sensing fiber length. In this paper, we demonstrate an amplitude modulated pulses based phase-sensitive OTDR to detect vibrations with high spatial resolution and wide frequency response range. The amplitude modulated pulses consisting of narrow pulses and background light are injected into the sensing fiber as probe light. The Rayleigh backscattering generated by the background light interferes at the detection end, presenting a phase sensitive response to external vibrations. The Rayleigh backscattering of narrow pulses are tracked to locate vibrations. The frequency information is obtained from the frequency domain analysis of the interference signal. The system can realize high frequency response with low repetition rate of probe pulses by one-end detection., Comment: 6 pages,8 figures

In fiber-optic distributed sensing, vibration signals are mostly assumed to follow Gaussian distribution for the simplicity of signal processing. However, in real applications, vibration signals often behave as non-Gaussian processes, which have rarely been highly considered. In this paper, a higher-order cumulants algorithm based phase-sensitive optical time-domain reflectometry (OTDR) is proposed to detect and analyze non-Gaussian vibration signals accompanied with noises. When disturbances are applied on the sensing fiber, the distribution probability of Rayleigh backscattering signals will deviate from the ideal Gaussian distribution. The non-Gaussian vibration is then extracted from Gaussian noises based on the probability density distribution. Simulations and experiments are carried out. The experimental results show that the demonstrated method can measure non-Gaussian vibrations with improved signal-to-noise ratio and spatial resolution., Comment: 6 pages,9 figures