Wavelet Uniform Quantization with Huffman Entropy Coding for Image Compression

This is an image compression program utilizing wavelet uniform quantization and Huffman entropy coding, designed to analyze the subject image Lena.bmp. The program performs comprehensive image compression to significantly reduce file size while maintaining visual quality. The implementation involves discrete wavelet transform (DWT) decomposition using filters like Haar or Daubechies, followed by uniform quantization that discretizes wavelet coefficients using predetermined thresholds. The Huffman entropy coding algorithm then assigns variable-length codes based on symbol frequency, prioritizing more frequent coefficients with shorter codes. Key functions include wavelet decomposition (wavedec2), quantization matrix application, and Huffman dictionary generation. Through this program, users can effectively study and understand fundamental image compression principles, including transform coding, quantization techniques, and entropy optimization methods. The code structure allows for parameter adjustment of quantization levels and wavelet types to analyze compression ratio versus quality tradeoffs.