Compression and Decompression Using Wavelet Transform and Zerotree Algorithm

This article presents a MATLAB-based compression and decompression program utilizing wavelet transform and the zerotree algorithm. We provide a detailed explanation of the algorithm's working principles, including wavelet decomposition for multi-resolution analysis and zerotree coding for efficient coefficient representation. The implementation covers key MATLAB functions such as wavedec2 for 2D wavelet decomposition and custom functions for zerotree encoding/decoding. We discuss the algorithm's advantages in preserving image quality during compression and its limitations in computational complexity. The article also compares this approach with other compression algorithms like JPEG and SPIHT, analyzing their respective strengths and weaknesses. Through this discussion, readers will gain comprehensive knowledge about compression algorithms and practical skills for implementing them in MATLAB, including threshold selection for coefficient quantization and run-length encoding of zerotree symbols.