MATLAB Implementation of Huffman Encoding and Decoding

This project involves developing a Huffman encoding decompression program using MATLAB, designed to decompress English text files. Huffman coding is an efficient compression algorithm that assigns shorter codes to frequently occurring characters, thereby reducing overall file size. The implementation includes building a Huffman tree using MATLAB's data structures, where the algorithm processes character frequencies through priority queues (implemented via min-heaps) to generate optimal prefix codes. Key programming components include: calculating character probability distributions from input text, constructing binary trees using MATLAB's struct arrays or object-oriented programming, and implementing bit-level operations for encoding/decoding. The decompression algorithm reverses this process by reading compressed bitstreams and traversing the Huffman tree to reconstruct original characters. This practical implementation helps deepen understanding of Huffman coding principles while demonstrating MATLAB's capabilities in handling bit manipulation and tree data structures. Through this program, users can learn to apply Huffman coding to real-world text compression tasks, enhancing their skills in data compression algorithms and MATLAB programming techniques. The code includes functions for frequency analysis, tree generation, encoding compression, and decoding reconstruction with proper error handling for invalid inputs.