Abstract

The rapid growth of geographic information technologies in the field of processing and analysis of spatial data has led to a significant increase in the role of geographic information systems in various fields of human activity. However, solving complex problems requires the use of large amounts of spatial data, efficient storage of data on on-board recording media and their transmission via communication channels. This leads to the need to create new effective methods of compression and data transmission of remote sensing of the Earth. The possibility of using fractal functions for image processing, which were transmitted via the satellite radio channel of a spacecraft, is considered. The information obtained by such a system is presented in the form of aerospace images that need to be processed and analyzed in order to obtain information about the objects that are displayed. An algorithm for constructing image encoding–decoding using a class of continuous functions that depend on a finite set of parameters and have fractal properties is investigated. The mathematical model used in fractal image compression is called a system of iterative functions. The encoding process is time consuming because it performs a large number of transformations and mathematical calculations. However, due to this, a high degree of image compression is achieved. This class of functions has an interesting property—knowing the initial sets of numbers, we can easily calculate the value of the function, but when the values of the function are known, it is very difficult to return the initial set of values, because there are a huge number of such combinations. Therefore, in order to de-encode the image, it is necessary to know fractal codes that will help to restore the raster image.

Highlights

  • Remote sensing of the Earth (REE) is the observation of our planet and the determination of the properties of objects on the earth’s surface, obtained with the help of imaging devices installed on aircraft and artificial satellites of the Earth (Figure 1)

  • The aim of our research is to model the class of fractal functions, study their properties and establish the possibility of their application for an efficient algorithm for encoding images that are presented in digital form

  • Fractal encoding is a mathematical process for encoding rasters into a set of mathematical data that reproduces the fractal properties of a given image

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Summary

Introduction

Remote sensing of the Earth (REE) is the observation of our planet and the determination of the properties of objects on the earth’s surface, obtained with the help of imaging devices installed on aircraft and artificial satellites of the Earth (Figure 1). The obtained data are aerospace images of the observed part of the earth’s surface in digital form in the form of raster images (Figures 2 and 3). These data are subject to further detailed analysis, namely, the determination of quantitative characteristics of the object under study, which are necessary to predict the development of a phenomenon or process. The amount of this graphical information is very large and needs to be compressed when transmitting data over communication channels and used in geographic information systems

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