The paper provides a model for selecting satellite systems for optical observation of the Earth by the probability of recognizing objects. The model is based on improved rules for selecting satellites by the spatial resolution of onboard imaging system. The model advantage over the known ones is the satellite systems selection not only due to the spatial resolution of image, but also taking into account the predictable contrast of objects and the required recognition level. The proposed model ensures a more correct pre-selection of satellite systems, in doing so reducing the cost of satellite imaging by preventing extra-requirements for spatial resolution of onboard imaging system. Also, the article proposes a method of forming a database of radiometric contrasts of typical objects and backgrounds for their consideration in the model for choosing satellite systems. This method does not depend on the specific types of on-board equipment, as well as on the availability of archival images at the time of planning satellite imagery.
The object of research is the process of segmentation of optoelectronic images acquired from space observation systems. The method of segmentation of optoelectronic images acquired from space observation systems based on the firefly algorithm, unlike known ones, involves the following:
– the pre-selection of brightness channels of the Red-Green-Blue color space in the original image;
– calculation of the level of luminosity for each firefly;
– assigning each firefly with the neighboring firefly, within a certain radius, whose level of luminosity is higher than the natural level of luminosity of the firefly;
– determination of the coordinate of the updated position of the firefly in each brightness channel.
An experimental study into the segmentation of optoelectronic images acquired from space observation systems based on the firefly algorithm was carried out. It is established that the improved segmentation method based on the firefly algorithm allows for the segmentation of optoelectronic images acquired from space observation systems.
The quality of segmentation of optoelectronic images by the method based on the firefly algorithm was evaluated in comparison with methods based on the particle swarm algorithm and the Sine-Cosine algorithm. It was found that the improved method based on the firefly algorithm reduces the segmentation error of the first kind by an average of 11 % and the segmentation error of the second kind by an average of 9 %. This becomes possible by using the firefly algorithm.
Methods of image segmentation can be implemented in software and hardware systems for processing optoelectronic images acquired from space surveillance systems.
Further studies may focus on comparing the quality of segmentation method based on the firefly algorithm with segmentation methods based on genetic algorithms.
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