EFFICIENCY OF LOSSLESS DATA COMPRESSION ALGORITHM MODIFICATION

Abstract

The current level of development of information technologies causes a rapid increase in the amount of information stored, transmitted and processed in computer systems. Ensuring the full and effective use of this information requires the use of the latest improved algorithms for compaction and optimization of its storage. The further growth of the technical level of hardware and software is closely related to the problems of lack of memory for storage, which also actualizes the task of effective data compression. Improved compression algorithms allow more efficient use of storage resources and reduce data transfer time over the network. Every year, programmers, scientists, and researchers look for ways to improve existing algorithms, as well as invent new ones, because every algorithm, even if it is simple, has its potential for improvement. A wide range of technologies related to the collection, processing, storage and transmission of information are largely oriented towards the development of systems in which graphical presentation of information has an advantage over other types of presentation. The development of modern computer systems and networks has influenced the wide distribution of tools operating with digital images. It is clear that storing and transferring a large number of images in their original, unprocessed form is a rather resource-intensive task. In turn, modern multimedia systems have gained considerable popularity thanks, first of all, to effective means of compressing graphic information. Image compression is a key factor in improving the efficiency of data transfer and the use of computing resources. The work is devoted to the study of the modification of the data compression algorithm The Quite OK Image Format, or QOI, which is optimized for speed for the compression of graphic information. Testing of those implementations of the algorithm, which were proposed by its author, shows such encouraging results that it can make it competitive with the already known PNG algorithm, providing a higher compression speed and targeting work with archives. The article compares the results of the two proposed modifications of the algorithm with the original implementation and shows their advantages. The effectiveness of the modifications and the features of their application for various cases were evaluated. A comparison of file compression coefficients, which were compressed by the original QOI algorithm, with such coefficients, which were obtained as a result of the application of modifications of its initial version, was also carried out.