MATLAB Implementation of Contourlet Transform Source Code

The Contourlet Transform is an advanced multiscale geometric analysis tool that extends traditional wavelet transforms by effectively capturing directional information in images. This MATLAB implementation provides a complete framework for image decomposition and reconstruction using pyramidal directional filter banks. The code typically involves key functions such as: 1. Pyramidal decomposition using Laplacian pyramid filters 2. Directional filtering through DFB (Directional Filter Bank) stages 3. Multi-scale directional decomposition configuration Implementation typically requires MATLAB's Signal Processing Toolbox and involves parameters like decomposition levels (pyramid level) and directional subdivisions (directional level). The core algorithm processes images through iterative downsampling and directional filtering, where each directional subband captures specific orientation features. Users should note that proper parameter selection (usually 3-4 pyramid levels with 8-16 directions per scale) is crucial for optimal performance in applications like image denoising, compression, and feature extraction. While Contourlet Transform excels in representing contours and textures, it's important to evaluate its computational complexity compared to other transforms like curvelets or shearlets for specific tasks. The MATLAB implementation generally includes visualization functions to display directional subbands and reconstruction error analysis.