This article is a report on the results of a comparative analysis of various most commonly used methods of fractal image compression: actually, fractal compression, compression using iterated functional systems, compression based on quad trees. Nowadays, when huge amounts of data are generated daily, efficient image compression techniques play an important role in reducing the required storage space and transmission bandwidth. Fractal compression, a relatively new approach, attracts attention due to its ability to compress images with minimal loss of quality. Therefore, when comparing the above compression methods, the following criteria were used: compression ratio, processing efficiency (productivity), and the quality of the images obtained. The article also discusses the basic principles of fractal compression, its advantages and disadvantages compared to traditional methods such as JPEG and PNG. Special attention is paid to the analysis of various fractal compression algorithms, their application and performance. The authors of the article strive to identify the most effective methods that provide a high degree of compression while maintaining the maximum amount of information about the image. This analysis can be useful for developers, engineers and researchers involved in image and data processing, as well as for a wide range of readers interested in advanced technologies in the field of digital data processing.
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