COMPARISON OF OPTIMIZED GEOINFORMATION DATA INTERPOLATION METHODS

Abstract

With the development of information technologies, geographic information systems penetrate into various fields of science. This results in more frequent transmission of large amounts of data. When exchanging such data, part of it is often damaged or lost, which leads to the need to restore them. The field of application of geographic information systems is constantly expanding and covers new areas of science, production technologies, social life, etc.

In robots, a variety of methods of interpolation on the application of geoinformation images are looked at. Some results and shortcomings of such types are shown, such as multi-quadratic, inverted, Gaus, line, cubic. The adjustment and establishment of the method is based on the criteria for speed and accuracy in the iteration process. The analysis of the last days was taken into account for the duration of the last days, when the parameters were assessed. For the analysis of the cob image, a software lock has been broken up, so that the image for these types of approximation and the accuracy and speed of methods has been updated. For the input file, a file in the * .json format is looked at, which is rendered on the basis of data from the Institute of Geochemistry of the National Academy of Sciences of Ukraine ancestry, Poltava region". For the development of the software Python software. The vast libraries of the mobile library provide a wide range of possibilities for optimizing graphical data and saving them in json text format.

Кeceived in the course of the last data show, with the most precise methods of updating the image є the methods of fractal approximation and Quantum. The hour of calculation is increased for the Quantum method in accordance with the other methods. For updating the data for the  * .json file, the best result is given by the Kvіntіk method. For the processing of the great arrays of tributes in the docile vicorist methods of cubic interpolation.

Keywords. Image recovery, interpolation, geoinformation data, fractal approximation, interpolation accuracy, GIS.