Abstract
The article discusses the methods of swarm intelligence, namely, an improved method based on the ant colony optimization and the method of an artificial bee colony. The goal of the work is to carry out a comparative assessment of the optical-electronic images segmentation quality by the ant colony optimization and the artificial bee colony. Segmentation of tonal optical-electronic images was carried out using the proposed methods of swarm intelligence. The results of the segmentation of optical-electronic images obtained from the spacecraft are presented. A visual assessment of the quality of segmentation results was carried out using improved methods. The classical errors of the first and second kind of segmentation of optoelectronic images are calculated for the proposed methods of swarm intelligence and for known segmentation methods. The features of using each of the proposed methods of swarm intelligence are determined. The tasks for which it is better to use each of the proposed methods of swarm intelligence are determined.
Highlights
Today, data of the remote sensing of the Earth have become available to a wide range of users
The goal of this work is carrying out comparative assessment of the optical-electronic images segmentation quality by the ant colony optimization and the artificial bee colony
An improved method based on ant colony optimization and an artificial bee colony method are discussed
Summary
Data of the remote sensing of the Earth have become available to a wide range of users. They are actively used for many purposes in the fields of life. Scientific and technical achievements in the field of creation and development of space remote sensing systems, technologies for obtaining, processing and thematic interpretation of data have many times expanded the list of tasks that are solved with their help [1]. Most data of the remote sensing of the Earth is obtained from space. Data of the remote sensing of the Earth are raster optical-electronic images presented in digital form. Their processing and interpretation is closely related to digital image processing
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