M.A. Kryachko1

1 Saint-Petersburg State University of Aerospace Instrumentation (St. Petersburg, Russia)

1 JSC "Lukoil-Technologies" (Moscow, St. Petersburg, Russia)

1 mike_kr@mail.ru

The problem of processing large data arrays is considered. Development of effective algorithms is the basis of successful application of new technologies. Complexity of the algorithm and accuracy of the results are the key quality indicators. The use of compact carrier functions leads to a decrease in processing time and complexity of the numerical algorithm. The accuracy of the data representation and the correctness of the results mainly depend on the approximation properties. It follows that a combination of the above characteristics is necessary to create efficient algorithms for processing large data sets.

Aim of article – to develop and evaluate the possibilities of application of generalised wavelets based on Kravchenko-Rvachev functions for image processing with a given quality on the basis of the analysis of the quality loss control mechanism. Discrete image compression by Kravchenko-Rvachev functions possessing such fundamental qualities as good approximation properties, high order of smoothness and existence of a basis with a local carrier in spaces of atomic functions is considered. Since the generalised up-functions have the same properties, similar compression results can be obtained using the generalised discrete atomic transform, which is based on their application, which is a promising direction in digital image processing. The presented method of image processing can be used for various purposes, including reducing the size of data before their transmission through the communication channel from the sensor to the point of reception via a communication line with limited bandwidth, for storing the received images for their further use in the centres of information processing of remote sensing of the earth, as well as for data transmission to potential users.

Kryachko M.A. Application of generalised atomic wavelets in image processing problems. Information-measuring and Control Systems. 2024. V. 22. № 4. P. 69−76. DOI: https://doi.org/10.18127/j20700814-202404-08 (in Russian)

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