Multi-Level Wavelet Decomposition for Image Analysis

This program serves as a highly practical tool for performing multi-level wavelet decomposition on images. Through hierarchical decomposition, it extracts wavelet coefficients from each sub-band, enabling detailed analysis of image characteristics and fine details. The implementation typically utilizes pyramid algorithm structures with filter banks (e.g., Daubechies wavelets) through functions like wavedec2() in MATLAB, which recursively applies decomposition to approximation coefficients. This functionality supports advanced research and exploration in image processing and analysis by revealing frequency-domain information at multiple resolutions. The program features user-friendly parameter configuration for decomposition levels (e.g., setting n=3 for 3-level decomposition) and wavelet type selection, allowing customization according to specific research requirements. Ultimately, this tool facilitates deeper understanding and utilization of image information, expanding possibilities for both academic research and practical applications in fields like compression and feature extraction.