Evidence of an upper ionospheric electric field perturbation correlated with a gamma ray burst

Earth's atmosphere, whose ionization stability plays a fundamental role for the evolution and endurance of life, is exposed to the effect of cosmic explosions producing high energy Gamma-ray-bursts. Being able to abruptly increase the atmospheric ionization, they might deplete stratospheric ozone on a global scale. During the last decades, an average of more than one Gamma-ray-burst per day were recorded. Nevertheless, measurable effects on the ionosphere were rarely observed, in any case on its bottom-side (from about 60 km up to about 350 km of altitude). Here, we report evidence of an intense top-side (about 500 km) ionospheric perturbation induced by significant sudden ionospheric disturbance, and a large variation of the ionospheric electric field at 500 km, which are both correlated with the October 9, 2022 Gamma-ray-burst (GRB221009A).

Look-up table (LUT) method for inverse halftoning

In this paper we propose look-up table (LUT) based methods for inverse halftoning of images. The LUT for inverse halftoning is obtained from the histogram gathered from a few sample halftone images and corresponding original images. The method is extremely fast (no filtering is required) and the PSNR and visual image quality achieved is comparable to the best methods known for inverse halftoning. The LUT inverse halftoning method does not depend on the specific properties of the halftoning method, and can be applied to any halftoning method. Then, an algorithm for template selection for LUT inverse halftoning is introduced. We demonstrate the performance of the LUT inverse halftoning algorithm on error diffused images and ordered dithered images. We also extend LUT inverse halftoning to color halftones.

Optimized halftoning using dot diffusion and methods for inverse halftoning

Unlike the error diffusion method, the dot diffusion method for digital halftoning has the advantage of pixel-level parallelism. However, the image quality offered by error diffusion is still regarded as superior to most of the other known methods. We show how the dot diffusion method can be improved by optimization of the so-called class matrix. By taking the human visual characteristics into account we show that such optimization consistently results in images comparable to error diffusion, without sacrificing the pixel-level parallelism. Adaptive dot diffusion is also introduced and then a mathematical description of dot diffusion is derived. Furthermore, inverse halftoning of dot diffused images is discussed and two methods are proposed. The first one uses projection onto convex sets (POCS) and the second one uses wavelets. Of these methods, the wavelet method does not make use of the knowledge of the class matrix. Embedded multiresolution dot diffusion is also discussed, which is useful for rendering at different resolutions and transmitting images progressively.