Noise-resistant complexing of multi-and hyperspectral images in optoelectronic information support systems for modern and prospective helicopters

DOI: 10.34759/trd-2020-110-12

Аuthors

Shipko V. V.

Air force academy named after professor N.E. Zhukovskii and Y.A. Gagarin, Voronezh, Russia

e-mail: shipko.v@bk.ru

Abstract

Currently, multi-channel Earth surface monitoring systems both air- and space based are being intensively developed. Helicopter information support systems (pilot survey, search survey, and sighting), which include multispectral and, in the future, hyperspectral optical radiation sensors that will be integrated into a single information system, are of no exception. Application of hyperspectral photography allows increase the detection and recognition efficiency of scene objects. In turn, while hyperspectral photography, the detected radiation is being split into hundreds of components of the generated hyperspectral image, which leads to a significant decrease in the level of the useful signal in relation to noise. Hyperspectral images are subjected to additive uncorrelated noise, which can reach high levels. At the same time, there are quite strict requirements for high spatial resolution of such complexes.

There are many image processing techniques and technologies, and one of the most important areas of processing multi- and hyperspectral images is their complexing.

The article considers an algorithm for multispectral images complexing in conditions of additive Gaussian noise, based on the interchannel gradient reconstruction technique. The proposed algorithm allows eliminate highly dispersed values of noise amplitudes in the multispectral image spectral components while their complexing. It also allows increasing the local contrast of the resulting image, containing elements of the original images of the same scene, obtained in different spectral ranges, while preserving the contour features of objects from all the spectral components of the multispectral image and the brightness portrait of the priority spectral component. The article presents examples of complex images and results of numerical studies, confirming the effectiveness of the proposed method are presented.

Keywords:

multispectral images, hyperspectral images, complexing, additive noise, optoelectronic systems

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