MATLAB Implementation of JPEG Compression with Uniform Quantization and Huffman Coding

This documentation presents a complete MATLAB implementation of JPEG compression. The source code systematically combines two core components: uniform quantization for frequency domain compression and Huffman encoding for entropy compression. The implementation follows standard JPEG workflow including color space conversion (RGB to YCbCr), discrete cosine transform (DCT) on 8x8 blocks, quantization using standard JPEG quantization tables, and Huffman coding for efficient data representation. The code provides a practical approach to image compression by allowing users to adjust compression levels through quantization parameters. Key functions include matrix operations for DCT computation, quantization table scaling, and Huffman tree generation for optimal coding efficiency. The implementation maintains a balance between compression ratio and image quality preservation. Both beginners and experienced programmers can utilize this code to understand JPEG compression mechanics, experiment with different compression settings, and analyze the impact of quantization on image quality. The well-commented code structure makes it suitable for educational purposes and practical image compression applications. This implementation serves as an excellent resource for studying digital image processing algorithms and developing customized compression solutions.