Integration of the image in the case of manifold lightless appliances
DOI:
https://doi.org/10.30837/rt.2020.2.201.10Keywords:
unmanned aerial vehicle, image, integration, detection, recognition, quality criterionAbstract
The most promising direction for solving the urgent task of detecting and tracking unmanned aerial vehicles (UAVs) is the use of a multispectral optoelectronic system for acquiring and integrating images of different wavelength ranges. In practice, taking into account the peculiarities of spectrozonal processing and image formation, it becomes necessary to implement a complex multi-stage procedure for obtaining, assessing quality, making decisions about the possibility of using the resulting images and their immediate subsequent complex use.
The article considers the task of complexing images in the visible and near infrared ranges when UAVs are detected. It is shown that it is advisable to perform the integration at the level of channel decisions, or by forming a combined image. In this case, the accuracy of combining the fields of view of multispectral sensors is important.
At the stage of forming a generalized image, it is advisable to use formalized informational criteria that sufficiently reflect the subjective value of the images. When obtaining the resulting image, it is preferable to use the weight function method, which allows combining channels using a priori information about their value, as well as on the basis of adaptation to changing input information. Among the methods of complexing by decomposing images into a spectrum, the most preferable is the method using wavelet transform, since it allows you to obtain information about objects in the spatial-frequency representation. If poorly formalized partial images enter the channels of the processing system, then a trained two-level complexing scheme should be used.
It is shown that the integration process increases the information content of the resulting image when using UAVs in comparison with the images obtained in individual channels of the system and provides significant qualitative and quantitative advantages in solving problems of detection, discrimination, recognition, tracking and target designation.References
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