Huffman Encoding and Decoding Implementation in MATLAB
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In this documentation, we present a MATLAB implementation of the Huffman encoding and decoding algorithm. This executable implementation demonstrates a practical data compression technique that efficiently reduces data size for optimal storage and transmission. The core algorithm builds a variable-length prefix code based on character frequencies, where more frequent characters receive shorter codes. Our implementation includes key functions for building the Huffman tree using a priority queue approach, generating optimal codes through tree traversal, and handling both encoding and decoding processes. The code features probability calculation, binary tree construction using MATLAB's built-in data structures, and bit-level operations for efficient compression. This practical example helps deepen understanding of Huffman coding principles, including entropy reduction and prefix code properties. Let's begin exploring this efficient lossless compression technique!
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