Peculiarities of registration of magnetic field variations by a quantum sensor based on a ferrofluid cell

Logunov, S. E.; Давыдов, В. В.; Vysoczky, M. G.; Titova, O. A.

doi:10.1088/1742-6596/1135/1/012069

Cited by 21 publications

(1 citation statement)

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“…That is why optical sensors with different technical characteristics are the basis of helicopter optoelectronic systems (OES). OES are designed to support piloting and landing of a helicopter, observing of the surrounding space and detecting the objects of interest (Logunov et al, 2018). However, the quality of obtained optical images depends on the conditions of illumination and transparency of the atmosphere, which significantly complicates their use at night, as well as in fog, rain, snow.…”

Section: Introductionmentioning

confidence: 99%

Adaptive Matching of the Radar Signal and Image Display Device Dynamic Ranges

Garmash¹,

Petrov²,

Andreev³

et al. 2019

Int J Math, Eng, Manag Sci

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This article presents nonlinear radar signal processing method to form an image of the Earth's surface. The method proposes to match the dynamic ranges of the received signal and of the visualization device. The essence of the method is adaptive nonlinear signal processing, which provides better local contrast of radar images and improves discrimination of individual objects. The computational complexity of the proposed algorithm is optimized and allows real-time implementation in the airborne computing systems with limited computational power. Objects with large RCS merged into large illuminated "spots"; their visibility on the surrounding background has been reduced, unwanted effects are due to the fact that the above algorithms have a single point effect. To overcome the problems, the «Retinex» algorithm is usually used. They do not take into account the local neighborhood of pixels; therefore, in cases where the image contains both highly dark and strongly light local areas, these algorithms cannot provide high-quality matching of dynamic ranges.

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Section: Introductionmentioning

confidence: 99%