Beamlet Transform Toolbox

The Beamlet Transform Toolbox serves as an invaluable resource for leveraging beamlet-related knowledge through practical implementation. This toolbox provides robust algorithms for performing beamlet decomposition and reconstruction, featuring key functions for multi-scale geometric analysis. Users can access optimized code implementations for beamlet thresholding, edge detection, and directional filtering operations. The package includes detailed examples demonstrating beamlet-based image processing techniques, along with exercises covering sparse representation and adaptive approximation methods. Whether you're beginning with beamlet theory or advancing existing expertise, this toolbox offers essential guidance through commented MATLAB/Python scripts and performance-optimized algorithms. Furthermore, it contains numerous practical cases illustrating beamlet applications in seismic data interpretation, medical imaging, and computer vision. Complete with benchmarking datasets and visualization utilities, this toolbox enables mastery of beamlet transforms through hands-on coding experience. Don't miss this opportunity to enhance your beamlet computational skills!