Implementing Huffman Coding for Data Compression

This paper provides a thorough comparison between the Quaternary Tree Structure and M-Gram Entropy Variable to Variable Coding variations of the traditional Huffman data compression algorithm. The main goal is to analyze the original Huffman algorithm's binary tree code structure and compare it with the quaternary tree structure used in quaternary tree compression. Furthermore, the paper explores the theoretical foundation and application of the novel M-Gram Entropy Variable to Variable Coding method. By closely examining encoding processes, decoding mechanisms, and compression effectiveness, this work seeks to clarify the unique features and comparative advantages of each technique. This work aims to offer useful insights for data compression researchers and practitioners by illuminating the trade-offs between compression ratio, computational complexity, and adaptation to various data kinds.