MATLAB-based Huffman Encoding and Decoding Program for Images and Sequences

This MATLAB program implements Huffman encoding and decoding for images and data sequences. Huffman coding is a widely-used lossless data compression algorithm that reduces storage requirements and transmission bandwidth by assigning variable-length codes to input symbols based on their frequency of occurrence. The implementation includes key components such as frequency probability calculation, Huffman tree construction using priority queues, code generation through tree traversal, and efficient encoding/decoding processes. For image processing, the program handles pixel value distribution analysis and can process both grayscale and color images by treating pixel intensities as symbols. Sequence data processing involves analyzing character or numerical value frequencies. Key MATLAB functions employed include histcounts for frequency analysis, custom heap data structures for tree building, and bit-level operations for compact code representation. The program demonstrates practical compression ratios while maintaining perfect data reconstruction through proper decoding implementation. This implementation serves as an educational tool for understanding Huffman coding principles, including entropy reduction, prefix code properties, and optimal compression techniques. Users can apply this to practical scenarios involving image compression, text data reduction, and communication systems requiring efficient data transmission. The code includes visualization components to display compression statistics and tree structures for better algorithmic understanding.