Vortex lines of the electromagnetic field

Relativistic definition of the phase of the electromagnetic field, involving two Lorentz invariants, based on the Riemann-Silberstein vector is adopted to extend our previous study [I. Bialynicki-Birula, Z. Bialynicka-Birula and C. Sliwa, Phys. Rev. A 61, 032110 (2000)] of the motion of vortex lines embedded in the solutions of wave equations from Schroedinger wave mechanics to Maxwell theory. It is shown that time evolution of vortex lines has universal features; in Maxwell theory it is very similar to that in Schroedinger wave mechanics. Connection with some early work on geometrodynamics is established. Simple examples of solutions of Maxwell equations with embedded vortex lines are given. Vortex lines in Laguerre-Gaussian beams are treated in some detail.Comment: 11 pages, 6 figures, to be published in Phys. Rev.

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Climatic and atmospheric phenomena – such as haze, fog and smoke – may lead to deterioration of quality and poor scenic clarity of outdoor images. In computer graphics, the authors can model these images as a linear combination of scene radiance, medium transmission and airlight. Several techniques have been proposed to remove the effects of haze from images using this model. The most effective approach for removing the haze effect from a single image is based on dark channel prior. Dark channel prior is based on statistical observation of outdoor images comprising some regions with dark intensity pixels. Here we propose a new l2‐norm‐based prior to generate a dark channel in order to remove the haze from a single‐input image. The dark channel generated using this new prior is more robust and free from the block‐effect. We also propose a statistical technique for airlight estimation of a given image. The proposed technique for modifying the dark channel prior and the airlight estimation are robust techniques as compared with approaches detailed in currently available literature. By combining this modified dark channel and estimated airlight, the haze can be directly removed and a more accurate haze‐free image can be recovered from single‐input hazy image

Separating Transparent Layers through Layer Information Exchange

In this paper we present an approach for separating two transparent layers in images and video sequences. Given two initial unknown physical mixtures, I1 and I2 , of real scene layers, L1 and L2 , we seek a layer separation which minimizes the structural correlations across the two layers, at every image point. Such a separation is achieved by transferring local grayscale structure from one image to the other wherever it is highly correlated with the underlying local grayscale structure in the other image, and vice versa. This bi-directional transfer operation, which we call the "layer information exchange", is performed on diminishing window sizes, from global image windows (i.e., the entire image), down to local image windows, thus detecting similar grayscale structures at varying scales across pixels. We show the applicability of this approach to various real-world scenarios, including image and video transparency separation. In particular, we show that this approach can be used for separating transparent layers in images obtained under di#erent polarizations, as well as for separating complex non-rigid transparent motions in video sequences. These can be done without prior knowledge of the layer mixing model (simple additive, alpha-mated composition with an unknown alpha-map, or other), and under unknown complex temporal changes (e.g., unknown varying lighting conditions)