Static Image Compression Method based on the Huffman Algorithm

The problem of image compression remains relevant and in demand due to the increasing volume of images in today’s information society. The article examines lossless compression methods for static images. When using compression methods, the most important issues are the transformation and restoration of information, as well as the compression ratio. The authors propose a hybrid information compression method based on the Huffman algorithm which allows for the maximum utilization of the advantages of the Huffman algorithm in solving a range of tasks while mitigating its shortcomings. In the developed method, improvements are achieved by initially processing the image with another compression method – specifically, the dictionary-based LZW method. The proposed hybrid method allows to increase in the information compression ratio compared to the original methods and minimize dependency on the characteristics of the input images. An analysis of the developed hybrid method has been conducted and compared with the original methods. Recommendations have been developed for selecting the optimal method (Huffman, LZW, or the hybrid method) for solving various tasks.