Efficiency Evaluation of Huffman, Lempel-Ziv, And Run-Length Algorithms in Lossless Image Compression for Optimizing Storage and Transmission Efficiency

The usage of digital data has become increasingly common today, ranging from simple text documents to complex audio and image data.As the volume of data grows, the need for efficient storage solutions becomes crucial, as smaller storage reduces costs.While human memory is the cheapest storage, it is not compatible with computer data storage needs.This study investigates lossless image compression algorithms, which enable the exact reconstruction of original images from their compressed forms.Image compression is vital for reducing storage space and expediting data transmission over the Internet.This research focuses on a comparative analysis of three prominent algorithms: Lempel-Ziv, Run-length, and Huffman compression.The performance of these algorithms is evaluated based on their compression ratios, with their respective advantages and disadvantages discussed.The findings reveal that the Huffman algorithm is the most effective for compressing JPEG, PNG, and BMP image formats.Although the Lempel-Ziv algorithm is also suitable for these formats, it is less efficient than Huffman.This study underscores the importance of selecting appropriate compression algorithms to optimize storage and transmission efficiency.