MATLAB Implementation of EZW Encoding and Decoding Algorithm

This MATLAB implementation of the EZW (Embedded Zerotree Wavelet) encoding and decoding algorithm performs wavelet transformation on input images and achieves compression through systematic scanning of wavelet coefficient matrices. The implementation includes entropy encoding using Huffman coding to efficiently encode and decode image data. Key implementation features: - Wavelet transformation using MATLAB's wavelet toolbox functions (e.g., wavedec2 for 2D discrete wavelet transform) - EZW algorithm implementation that scans wavelet coefficients in multiple passes using zerotree data structure for efficient coefficient representation - Huffman coding module for entropy encoding of significant map and coefficient values - Progressive encoding capability allowing reconstruction at various quality levels The algorithm processes images by first decomposing them into wavelet coefficients, then applying the EZW scanning method to identify significant coefficients while leveraging parent-child relationships in wavelet trees. The Huffman encoding stage further compresses the output bitstream by assigning shorter codes to more frequent symbols.